The work that you’ll do:

• Build relationships with assigned customers, continually delight them with a positive, customer-centric attitude, and provide proactive strategy and guidance
• Work with customers to ensure they are leveraging SupportLogic effectively and finding value in our services
• Become an expert in our product and turn our customers into product champions
• Act as the voice of the customer internally; as the steward of the customer relationship, work cross-functionally with Sales, Product, and Engineering to ensure a consistent and strong customer message is embedded in processes
• Develop and share best practices with team members to continually improve the quality, effectiveness, and efficiency of our processes

What you will bring to the role:

• Bachelor’s degree and 3-5 years of experience in a customer-facing role, such as Customer Success, Customer Support or Account Management
• Understanding of customer success and technical support processes and tools with a desire to learn new technologies
• Experience working with senior and executive-level customer contacts
• Demonstrated ability and desire to work and excel in a fast-paced environment
• Well-organized, with close attention to detail and the ability to prioritize
• Experience with cloud-based customer support (Salesforce, Zendesk, Microsoft Dynamics), product analytics (Pendo, Google Analytics), and customer success (Gainsight, etc.) tools is a plus

The work that you’ll do:

• Deliver virtual end-user and administrator training webinars and workshops to SupportLogic Customers and Partners
• Become a subject matter expert for our products, as well as to the business domain of our customers
• Work cross-functionally to build and maintain training assets – presentations, videos, and other collaterals
• Mentor and coach training participants
• Work both independently and collaboratively

What you will bring to the role:

• Experience training or consulting internal (employees) and external (customers and partners) stakeholders on how to administer, configure, and use enterprise software products
• Knowledge of customer support processes and applications
• Excellent communication skills with a demonstrated aptitude for speaking to both a technical audience and a business user audience
• Experience maintaining curriculum and labs
• Comfortable with dynamic and changing priorities

The work that you’ll do:

• Lead the development of our customer education program
• Craft high-quality content that drives customer engagement and product usage
• Design customer learning paths and certification programs in collaboration with internal stakeholders and customers, supporting the following modes of education:
  • Instructor-led training
  • Videos and knowledgebase articles
  • Role-based self-paced courses
  • In-app tours
  • Initial and ongoing customer new hire onboarding
  • Certification/accreditation program

What you will bring to the role:

• Bachelor’s degree and prior experience in building learner-centric onboarding programs and instructional design
• You love customer education and can’t rest without ensuring all supporting content, programs, and processes are in-place
• You have a strong background in SaaS already in customer education, consulting, or support roles
• You are process-driven and know the importance of ensuring buy-in and adoption when rolling out new programs
• You are versed in building cross-functional partnership and alignment

An ideal candidate also has:

• Strong bias for action, the ability to think big, with insistence on high standards
• Direct experience working with major LMS systems (e.g., Docebo, Skilljar, Litmos)

The work that you’ll do:

• Connect and consult with existing customers in your portfolio on a regular cadence
• Prepare and present proposals and guide customers through the expansion/renewal process.
• Uncover new upsell and cross-sell opportunities, in collaboration with the Account Executives, in a fast-paced, value-driven environment
• Build and manage a strong pipeline of upsell & cross-sell opportunities while maintaining an accurate forecast
• Identify customers at risk and provide the support necessary to retain and make them successful.
• Work closely with your Customer Success Manager to ensure all success criteria are met during the customer’s lifecycle.

What you will bring to the role:

• 3-5 years of account management, sales, or customer success experience within a fast-paced startup environment preferred
• Demonstrated aptitude for both selling and building lasting relationships with customers
• Ability to establish credibility with an executive audience
• Problem-solving, analytical, and active listening skills
• Experience developing quantitative and qualitative analyses
• Confidence based on rigorous preparation and forethought
• Proven ability to achieve and exceed quotas and goals
• Ability to work individually and collaboratively to achieve set goals

The work you’ll do:

• Collaborate with customers and act as their trusted advisor on solving complex data science problems using SupportLogic
• Lead demonstrations, advise on and evaluate the viability of customer use cases, help develop success criteria, support Proof of Value trials, and quantify the business impact of data science solutions.
• Work side-by-side with the Sales, Engineering, and product teams to help our customers achieve their goals with SupportLogic.
• Manage multiple concurrent client projects / professional services engagements, including some directed at high-potential prospects during the sales process
• Act internally as the voice of the customer to the Product and Engineering teams

What you will bring to the role:

• 3-4 years of real-world customer experience in a data science role
• Experience collaborating with business stakeholders to ensure that machine learning solutions deliver successfully on business outcomes
• Hands-on experience with various machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.)
• Fluency with scripting in Python and experience with common data science libraries
• Familiarity with data platform technology integrations and tools for the manipulation of data
• S. degree in Computer Science, Mathematics, or similar quantitative field of study

Preferred Skills and Competencies:

• Experience with NLP for sentiment analysis and entity recognition and use of the SpaCy library
• Experience working on or with cloud platforms (AWS, GCP, Azure)

What you will be doing:

• Work with  Product Management and translate business requirements into technical deliverables.
• Architect, design and develop RESTful APIs and Microservices to ensure functional requirements are met and non-functional requirements are taken care of  e.g. quality, security, reliability, scalability, extensibility, testability, supportability, availability etc.
• Develop detailed API design specifications and documentation including API message schemas and process logic models describing process flows, aggregation, routing, transformation and error handling logic. Operationalize via throttling, caching, logging, analytics etc.
• Understand supporting polyglot persistence layer and defined data access strategies in consultation with Data-engineers. 
• Provide input in defining external APIs and Integration strategy to various 3rd party products in the ecosystem.
• Define API design standards, patterns and best practices. Lead API modelling and design activities in accordance with SOA and RESTful architecture principles.
• Participate in the Agile and DevOps including meetings, estimations, planning and design sessions
• Stay up to date on API development methodology, architecture design and technical standards, and translate them into effective business and client solutions
• Provide peer-review of solution designs and related code.

What you should have:

• 7+ years of experience preferred, including 3+ years hands-on API, Microservices and Integrations experience in development, implementation, and maintenance of complex business applications, that have a flushed out API-based glue layer.
• Proficiency in API design and implementation using development tools such as Postman, Swagger. Deep understanding of various Microservices and integration patterns using REST, HTTP(S), MQ, JSON, XML and SOAP.
• Deeply proficient in Python and SOA/Microservice Architecture (FastAPI, Flask, Django) and at least 1 other programming language (Scala or Java preferred).
• Good knowledge of OpenAPI spec, API security frameworks, token management and user access control using OAuth2, JWT etc. Experience of securing data with good understanding of PGP, SSH, OAuth, HTTPS, SFTP etc.
• Working knowledge of Data Lakes and Marts and good SQL knowledge to be able to debug Data issues with the polyglot persistence layer. 
• Prior experience creating consistent synthetic data sets for use in internal environments. 
• Knowledge of cloud and hybrid-cloud implementations including IaaS, PaaS and SaaS – GCP (preferred) and one of AWS/Azure.
• Solid hands-on experience on software development lifecycles (including working in agile and DevOps projects). Experience with a variety of modern programming languages and web-based development frameworks
• Experience with building externalized API’s and Integrations with 3rd party products are highly desired. 
• Demonstrated knowledge of test-driven development practices and experience with any of the version control tools such as GitHub, and Continuous Integrations with GCP Devops Services, Jenkins. Experience automating the CI/CD pipeline in conjunction with Devops will be a plus.
• Strong interpersonal and teaming skills — this is an extremely collaborative environment.
• Prior SaaS, startup experience and experience working with a distributed team.
• Exceptional written and verbal communication skills. Ability to work with some levels of ambiguity in terms of requirements.
• Worked with Agile development methodology and fluent with Git/Github (especially branching, merging, tagging).
• Bachelor’s degree in Computer Science, Engineering or related field, or equivalent training, fellowship, or work experience.

Nice-to-have skills & competencies: 

• Familiarity with Big-data technologies, ML/AI and specifically explainability issues in terms of presenting the AI prediction to end-users.
• Familiarity with the Support and Customer Success domain and software ecosystem.

What you will be doing:

• Cloud Strategy and Services: Define the cloud-strategy, whether a single cloud provider or multi-cloud or a variety of hybrid architectures. You are able to define Cloud-service adoption strategy (i.e. which Cloud-service we employ, versus adopting a 3rd party provider versus building inhouse), with strong data and reasoning. 
• Architecture and Standards: Set Cloud architectural standards (including applications, hardware & software) to ensure that new services and systems are implemented in-line with Support Logic’s architectural standards & security policies
• Security: Help deliver the DevSecOps roadmap and lead the operationalization. This includes external-facing production VPCs and their OAuth2.0 based access as well as internal environments and internal access to engineers/customer success who might have to trouble-shoot and maintain production applications and customer data. Be the interface with auditors when it comes to SOC2/ISO27001/HIPAA and other certifications. 
• Automation: Strong belief in infrastructure as code, with Terraform/Python/Jenkins based CI and CD automation. Ensure a containerized deployment
• Log Management & Monitoring: Implement an exhaustive APM scheme, so system and application metrics are exhaustively captured and acted upon in case of issues. Ensure Logs are rotated, aggregated and available to Development for monitoring. 
• Cost Management: Look for ways to deliver the same SLAs at lower cost (Investigate Serverless computing, Managed services, Autoscaling and other mechanisms) to ensure delivery at low cost.
• Coordination: Contribute meaningfully to application plans and help drive alignment with application teams, security,and business. Work with Sales/Customer Success in terms of producing appropriate collateral that may be needed when our customer InfoSec teams execute their due diligence. Participate in AGILE ceremonies to understand delivery expectations.

What you should have:

• A minimum of 7 years delivering Cloud-based platforms with GCP being a must and at least 1 other (Azure, AWS, Oracle-Cloud, Rackspace, VMWare Cloud etc.) and familiarity with other Data Center Technologies.  
• Strong knowledge of various IaaS, PaaS, SaaS offerings within GCP and other clouds with an ability to speak to pros/cons of going with a potential 3rd party, implementing natively on the cloud versus a managed service (from a technology and an economic perspective).
• Strong knowledge of various non-functional requirements and their associated SLAs (Scalability via Scaling up and Scaling out, Performance, Monitorability, Availability and so on).
• Strong experience with Containerization (Docker) and Container Orchestration (Kubernetes) 
• Extremely strong with scripting (one of Puppet/Chef/Ansible/Salt and or python, bash) and Terraform. Jenkins and other technologies to deliver high levels of automation and modern CI/CD pipelines. 
• Experience setting up and managing Escalations via integrations to PagerDuty or other similar mechanisms. Ability to set up a 24×7 follow the sun escalation and support model.
• Experience with Log Rotation, Management and Mining (via ELK, Splunk and other mechanisms)
• Experience setting up modern monitoring (3rd Party SaaS and/or Cloud-native services, Prometheus preferred).
• Prior Experience implementing a Call Rotation schedule and reacting to threats. 
• Strong interpersonal and teaming skills — this is an extremely collaborative environment.
• Prior SaaS, startup experience and experience working with a distributed team.
• Exceptional written and verbal communication skills. Ability to work with some levels of ambiguity in terms of requirements.
• Worked with Agile development methodology and fluent with Git/Github.
• Bachelor’s degree in Computer Science, Engineering or related field, or equivalent training, fellowship, or work experience.

Nice-to-have skills & competencies:

• Experience with Data Lake/Mart architectures, Data Technologies such as Google Big Query and administering 3rd Party cloud-agnostic Data products.
• Some knowledge of Machine Learning Operations and how to deploy and monitor data science models in production.

What you will be doing:

• Design systems that reliably transport and process millions of events per day in a continuously streamed architecture from Customer owned/administered Data Centers or clouds to SupportLogic Cloud presence. Sometimes, these could be 3rd party sources of data as well. Payload typically includes CRM data, Voice to Text Data, Conversational Data, Application Usage Data and several 10s of other data sources.
• Participate in the architecture, the roadmap and Build, Buy, Adopt OSS kind of decisions that can deliver Business SLAs at low cost. Ensure that the architecture in place can be responsive to business needs around 
  • Scale and Throughput
  • Pipeline accuracy and error handling.
  • Flexibility to support varied morphology of Data and life cycle events at source.
  • Velocity in terms of phased delivery….and so on.
• Implement systems that handle scale via smart distribution of compute responsibilities,  in a containerized environment.
• Provide real-time streaming and querying capability on this large volume of data and ensure that veracity checks are in place across the pipeline, so one can fail fast and autocorrect.
• Work closely with Data Scientists and Machine Learning engineers to solve data needs and incorporate algorithms and models into the pipeline. 
• At the same time work with customer success to deliver them tooling to aid with their participation in ETL/ELT pipelines: 
  • Customer Data Set Discovery.
  • Data Mapping to Canonical Data Representations.
  • Lights-out operations or self-service (to Customers): ensure inherent flexibility in the implementation, to handle customer specific variations in the shape of the incoming data or its transformation to canonical data representations.
• Work closely with Devops to understand the production behaviors of these pipelines and debug, troubleshoot performance or data correctness problems.
• Build Security at design time, via thinking through encryption @rest/in-motion, Access Control and other aspects.
• Documenting the data flow and perpetually be improving the pipeline in terms of cost, throughput, performance and automation.

What you should have:

• 5+ years’ experience building large-scale data pipelines and deploying these to production
• Deep knowledge of data structures, algorithms, distributed systems, and information retrieval (e.g. Elastic Search)
• Experience with polyglot persistence (RDBMS – OLTP and Star/Snowflake Schemas: PostgreSQL a plus, NoSQL e.g. Document DB and Columnar Data Stores, Hadoop and Spark ecosystem) and Cloud-native offerings (such as Cloud Data Warehouses: Snowflake and/or Redshift and/or Google BigQuery (preferred)).
• Deep experience with data lake/mart and modern architectures (Lambda, Kappa, etc.)
• Experience working with modern Messaging systems (Kafka, Google PubSub etc.)
• Experience with the latest in BI and AI-based BI with deep familiarity of at least a few vendor products (e.g. Google Data Studio, Thoughtspot, Sisense, Tableau etc.). 
• Highly familiar with Git/Github and implementing CI for Database code and schema. 
• Strong interpersonal and teaming skills — this is an extremely collaborative environment.
• Prior SaaS, startup experience and experience working with a distributed team.
• Exceptional written and verbal communication skills. Ability to work with some levels of ambiguity in terms of requirements.
• Worked with Agile development methodology and fluent with Git/Github (especially branching, merging, tagging).
• Bachelor’s degree in Computer Science, Engineering or related field, or equivalent training, fellowship, or work experience.

Nice-to-have skills & competencies:

• Experience with machine learning systems, their KPIs and ability to deploy them and build the virtuous 360 degree loop from production to model training. 
• A sense of the economics involved with numerous decisions that need to be made along the way to deliver at low costs/GB/year. 

The work you’ll do:

• Research – Develop new ML (and/or NLP) models and features, with an emphasis on driving value for customers and developing intellectual property (IP) for SupportLogic
• Integrate – Work with engineers to effectively transition models and features from research/notebooks to production settings
• Refine – Improve performance of existing models in a production setting by leveraging new approaches, features, and user feedback and/or telemetry
• Discover – Investigate, clean, analyze, and otherwise prepare new data sources for use in higher-order analysis or as input into machine learning models
• Collaborate – Work with members of ML, engineering, product, and customer-facing teams to map outside constraints with the correct modeling, analysis, and/or visualization approaches
• Communicate – Present results of research and/or analysis, typically using data visualization techniques, sometimes to broader audiences within or outside of SupportLogic

Qualifications:

• Located in the United States (due to customer data access requirements)
• 6+ years of professional software development experience
• 4+ years of experience as a full-time data scientist, machine learning researcher, or machine learning engineer
• B.S., degree in Computer Science, Mathematics, or similar quantitative field of study
• Fluency in Python and Jupyter notebooks
• Experience with common Python data science libraries such as Pandas, numpy, and scikit-learn
• Knowledge of a variety of machine learning techniques (NLP, clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages and drawbacks
• Experience with querying and using SQL
• Self-starting, with the interest and passion to contribute in a fast-paced startup environment

Preferences:

• Professional experience with NLP, especially transformers and/or transfer learning of pretrained language models
• Professional experience with deep learning and Python deep learning frameworks such as pytorch or tensorflow
• Experience with model management and deployment
• Experience with Docker
• Experience with sqlalchemy

What you will be doing: 

• Application Deployment Architecture: You collaborate with Development and Stakeholders to understand Application SLAs and design, implement, deploy and monitor the cloud-based infrastructure that will meet functional and non-functional requirements.
• Release: You understand how development is structured in terms of repositories and branching/merging and play a big role in ensuring releases move across environmental boundaries smoothly.
• Security: Help operationalize the DevopsSec roadmap. Play a leading role in the SOC2/HIPAA/ISO27001 and other certifications. 
• Coordination: Contribute meaningfully to application plans and help drive alignment with application teams, security,and business and participate in Sprint and Scrum ceremonies.
• Automation: Strong belief in infrastructure as code, with Terraform/Python/Jenkins based CI and CD automation. Ensure that internal environments are built the same way as external environments and ensure minimal to no environmental drift.
• Monitoring: You monitor the application and infrastructure in production and act on escalations and remediate whenever application SLAs are threatened. You ensure logs are rotated, stored and monitored so that engineering is well aware of application behavior in production.

What you should have:

• A minimum of 5 years delivering Cloud-based platforms with GCP being a must and at least 1 other (Azure, AWS, Oracle-Cloud, Rackspace, VMWare Cloud etc.) and familiarity with other Data Center Technologies.  
• Strong knowledge of various IaaS, PaaS, SaaS offerings within GCP and other clouds. Includes Machine Provisioning, Database Provisioning, Network Architecture and various other aspects involved in VPC design.
• Strong knowledge of various Non functional requirements and their associated SLAs (Scalability via Scaling up and Scaling out, Performance, Monitorability, Availability).
• Extremely strong with scripting (one of Puppet/Chef/Ansible/Salt and or python, bash) and Terraform. Jenkins and other technologies to deliver high levels of automation and modern CI/CD pipelines. 
• Deep knowledge of Containerization (Docker, Docker-Swarm, Kubernetes etc.)
• Experience with SIRP, SIEM and IDS/IPS/WAF solutions (Snort, Mod-Security in Open Source, Splunk/others in the paid realm).
• Experience with the latest in Authentication and Authorization (OAuth2, SAML, LDAP etc.) and experience with Auth0 and/or Okta or similar vendors.
• Strong interpersonal and teaming skills — this is an extremely collaborative environment.
• Prior SaaS, startup experience and experience working with a distributed team.
• Exceptional written and verbal communication skills. Ability to work with some levels of ambiguity in terms of requirements.
• Worked with Agile development methodology and fluent with Git/Github (especially branching, merging, tagging).
• Bachelor’s degree in Computer Science, Engineering or related field, or equivalent training, fellowship, or work experience.

Nice-to-have skills & competencies:

• Experience with Data Lake/Mart architectures, Data Technologies such as Google Big Query and administering 3rd Party Cloud Data Warehouses.
• Some knowledge of Machine Learning Operations and how to deploy and monitor data science models in production.

What you will be doing:

• Analyze our SDLC pipeline from Development to QA to Production to post-Production aspects, from the point of view of security. Define solutions needed to shore up secure access for end-users and internal employees alike and remediate potential vulnerabilities. 
• Ensure security best practices are followed when production VPCs are instantiated and operationalized. Ensure data is encrypted at rest and in motion. 
• Ensure best practices are followed vis-a-vis customer data handling, internal employee access to customer-data, production VPCs and  supporting infrastructure, based on principles of “least privilege”. Implement processes for streamlined Employee Provisioning (Onboarding/Offboarding), SSO (Single Sign On) and Cloud permissions. 
• Participate in routine threat detection (port scanning, penetration testing, CVE updates, Container Vulnerability Scans and so on) and remediate based on criticality. 
• Play a key role in working with auditors to ensure that we renew SOC2, ISO27001 and HIPAA certifications without duress, by implementing and practicing industry leading security, year around.
• Participate in Sprint Planning and Scrum ceremonies so that work gets operationalized in iterable chunks.
• Ensure that industry best practices are being followed across the board.
• Evaluate solutions from vendors and help us arrive at Build/Buy/Adopt OSS decisions.

What you should have:

• At least 5 years of experience working on a team with security responsibilities.
• In terms of cloud familiarity, GCP is a requirement and at least 1 more cloud provider is preferred.
• Experience automating and integrating security operations into DevOps processes.
• Deep Knowledge of containerization (Docker) and Container orchestration (Docker-Swarm, Kubernetes). Experience securing containerized applications.
• Deep knowledge of automation via Terraform and/or Python scripts. Experience with Chef/Puppet/Ansible and Jenkins to ensure that the CI/CD pipeline is secure. Understanding of industry standard release automation tools and processes.
• Experience with SIRP, SIEM and IDS/IPS/WAF solutions (Snort, Mod-Security in Open Source, Splunk/others in the paid realm).
• Experience with the latest in Authentication and Authorization (OAuth2, SAML, LDAP etc.) and experience with Auth0 and/or Okta or similar vendors.
• Strong interpersonal and teaming skills — this is an extremely collaborative environment.
• Prior SaaS, startup experience and experience working with a distributed team.
• Exceptional written and verbal communication skills. Ability to work with some levels of ambiguity in terms of requirements.
• Worked with Agile development methodology and fluent with Git/Github.
• Bachelor’s degree in Computer Science, Engineering or related field, or equivalent training, fellowship, or work experience.

Nice-to-have skills & competencies: 

• Familiarity with Big-data technologies, ML/AI and security concerns that arise from those implementations.

What you will be doing:

• Lead multiple PODs in terms of AGILE methodology adoption and becoming self-organized. Manage project scope/timelines to ensure smooth, on-time, within-budget delivery of features and capabilities. Participate in Backlog Grooming, Daily Standups, Sprint and Release Planning along with Retrospectives and other Ceremonies for multiple PODs. Be a strong advocate and change agent for the Agile/Scrum process and ceremonies.
• Collaborate with engineering, product leadership and key stakeholders such as sales, customer success to ensure alignment across teams to deliver on OKRs via a Data/KPI-driven approach. Be a point of contact for external communications (e.g. to customers, the Goto-market team and/or other stakeholders). Support the product management team, owner and provide education where needed.
• Help the product owner and development team remove impediments, achieve greater levels of AGILE maturity and deliver at good velocity and high quality. Help engineers manage their Scrum and/or Kanban style boards and backlogs and hold the team accountable to KPIs that further our OKRs.
• You will work to enhance your team’s skills in terms of estimation (T-shirt sizing and story) points and non-functional aspects such as good-architecture, performance, scalability, maintainability, monitorability, feature-flagging and A/B Testing. Experiment and encourage various Development methodologies to deliver at high velocity and quality (e.g. TDD, BDD etc.)
• Resolve conflicts and issues that occur. Escalate if plans are getting derailed and suggest ameliorations. Create an environment that empowers and energizes team members, with a focus on accountability, adaptability, and collaboration.
• Identify recurring issues and opportunities to improve engineering process, employees’ and business successes. Lead initiatives such as establishing KPIs that align with OKRs and ensure that automated CI/CD is enabled. Ensure that Git branching/merging is a smooth, well defined process. Keep a log of tech debt that might have accumulated and arrive at a plan to counter it.
• Attract and retain diverse talent by developing programs that support career development and recruiting strategies.

What you should have:

• 3+ years experience as a manager or team lead for cloud native, enterprise-grade,  SaaS development teams and with 5+ years experience in a hands-on technical role in a software development organization.
• Proficient with the entire SDLC, including successful product launches, as well as subsequent iterations of existing products, by utilizing effective software development practices including AGILE, CI/CD, Code-Review and reacting to SCA/SAST/DAST programs. 
• Have played a championing role in terms of AGILE and Scrum/Kanban adoption across the organization.
• Experience dealing with competing priorities in a fast-paced environment and quick thinking in terms of countering the “tyranny of OR” and phasing deliverables in quick iterations.
• Demonstrated track record of successfully hiring, managing, coaching and retaining engineers. 
• In-depth technical knowledge: 
  • Git/Github and branching/merging and repository management of engineering operations.
  • Strong experience implementing a unit-testing regime and automated integration testing. 
  • Good knowledge of SOA/Microservice/REST principles.
  • Proficient with UI/UX Design, React, Redux, Node.js based APIs.
  • Hands on experience with Python (with Flask/Django/Fast-API) and at least one other programming language (Scala, Go etc.). 
  • Good understanding of enterprise-integration, security-standards (Oauth2.0, SSO, encryption of data @ rest/in-transit and other non-functional requirements). 
  • Proficient with SQL against RDBMS (PostgreSQL preferred). 
  • Experience with messaging (Kafka, Google Pub-Sub, Rabbit MQ etc.)
  • Good understanding of polyglot persistence and NOSQL technologies and CDW (Cloud Data Warehouses)
  • Deep expertise with GCP (and one of Azure, AWS, Oracle Cloud etc.)
• Strong communication (written, verbal), interpersonal & mentoring skills
• Prior startup, SaaS, distributed team experience. 
• Expert knowledge of JIRA, Clickup (preferred) and/or another such technology.
• Experience with Scrum and Kanban at the very least.
• Familiarity with CI/CD, Automation, Git/Github, Release processes and GCP/AWS or another cloud environment. 
• You are a highly organized individual who truly believes in data driven decision making and is fanatical in terms of KPI measurement. Prior experience with OKRs and tying KPIs with OKRs

Nice-to-have skills and competencies:

• Expert knowledge of JIRA, Clickup (preferred) and/or another such technology.
• Familiarity with GCP (and one other cloud e.g. Azure, AWS)
• Scrum master or Cloud certification.
• Experience with Big-Data Technologies, Machine Learning, NLP and Data Science in general.

The work you’ll do:

• Ship – Increase velocity of ML model deployment into production through automation of model management, deployment, and rollout processes
• Validate – Increase confidence of model rollouts by enriching and automating model validation prior to and immediately after deployment
• Measure – Provide insight into accuracy and relevance of ML model predictions in production by measuring and monitoring model input and output data distributions, as well as user engagement/feedback on predictions
• Automate – Incorporate user feedback/activity into new ML model training by automation of data collection, model retraining, model measurement, etc., towards a goal of continuous automated model retraining
• Build – Provide internal tools or incorporate commercial tools (e.g., ClearML) into data scientist workflows for data analysis, feature generation, model development, etc., to boost ML team productivity
• Collaborate – Bridge the gap between ML research and production-grade backend code by working with other engineering teams to integrate new ML models or APIs into production

Qualifications:

• Located in the United States (due to customer data access requirements)
• 6+ years of professional software development experience
• 4+ years of professional experience as a full-time data scientist, machine learning researcher, or machine learning engineer
• 2+ years of professional experience working primarily on Natural Language Processing (NLP) modeling, model deployment, or analysis
• B.S., degree in Computer Science, Mathematics, or similar quantitative field of study
• Fluency in Python and Jupyter notebooks
• Experience with common Python data science libraries such as Pandas, numpy, and scikit-learn
• Experience with transfer learning of pretrained language models, particularly transformer-based models such as BERT
• Knowledge of a variety of NLP techniques and applications (NER, LDA, embeddings/vectors, etc.,) and their real-world advantages and drawbacks
• Experience with querying and using SQL
• Self-starting, with the interest and passion to contribute in a fast-paced startup environment

Preferences:

• Professional experience with NLP, especially transformers and/or transfer learning of pretrained language models
• Professional experience with deep learning and Python deep learning frameworks such as pytorch or tensorflow
• Experience with model management and deployment
• Experience with Docker
• Experience with sqlalchemy

The work you’ll do:

• Research – Develop new NLP models and features, with an emphasis on driving value for customers and developing intellectual property (IP) for SupportLogic
• Integrate – Work with engineers to effectively transition models and features from research/notebooks to production settings
• Refine – Improve performance of existing models in a production setting by leveraging new approaches, features, and user feedback and/or telemetry
• Discover – Investigate, clean, analyze, and otherwise prepare new data sources for use in higher-order analysis or as input into machine learning models
• Collaborate – Work with members of ML, engineering, product, and customer-facing teams to map outside constraints with the correct modeling, analysis, and/or visualization approaches
• Communicate – Present results of research and/or analysis, typically using data visualization techniques, sometimes to broader audiences within or outside of SupportLogic

Qualifications:

• Located in the United States (due to customer data access requirements)
• 6+ years of professional software development experience
• 4+ years of professional experience as a full-time data scientist, machine learning researcher, or machine learning engineer
• 2+ years of professional experience working primarily on Natural Language Processing (NLP) modeling, model deployment, or analysis
• B.S., degree in Computer Science, Mathematics, or similar quantitative field of study
• Fluency in Python and Jupyter notebooks
• Experience with common Python data science libraries such as Pandas, numpy, and scikit-learn
• Experience with transfer learning of pretrained language models, particularly transformer-based models such as BERT
• Knowledge of a variety of NLP techniques and applications (NER, LDA, embeddings/vectors, etc.,) and their real-world advantages and drawbacks
• Experience with querying and using SQL
• Self-starting, with the interest and passion to contribute in a fast-paced startup environment

Preferences:

• Professional experience with NLP, especially transformers and/or transfer learning of pretrained language models
• Professional experience with deep learning and Python deep learning frameworks such as pytorch or tensorflow
• Experience with model management and deployment
• Experience with Docker
• Experience with sqlalchemy

What you will be doing:

• Lead multiple PODs in terms of AGILE methodology adoption and enable them to become self-organized. Manage project scope/ delivery expectations.
• Conduct Backlog Grooming, Daily Standups, Sprint and Release Planning along with Retrospectives and other Ceremonies for multiple PODs.
• Help the teams manage their Scrum and/or Kanban style boards.
• Help the product owner and development team remove impediments, achieve greater levels of AGILE maturity and deliver at good velocity and high quality.
• Resolve conflicts and issues that occur.
• Support the product management team, owner and provide education where needed.
• Build out dashboards and maintain several KPIs at the individual POD and globally across PODs.
• Be the point of contact for external communications (e.g. from customers or stakeholders)
• Escalate if plans are getting derailed and suggest ameliorations. 

What you should have:

• Scrum master certification is required.
• Expert knowledge of JIRA, Clickup (preferred) and/or another such technology.
• Prior experience conducting Scrum Ceremonies and good soft skills vis-a-vis conducting meetings. Ability to think quickly and resolve conflict. 
• Ability to determine what is AGILE and what is not
• Knowledgeable in techniques to fill in gaps in the AGILE adoption.
• Experience with Scrum and Kanban at the very least.
• Familiarity with CI/CD, Automation, Git/Github, Release processes and GCP/AWS or another cloud environment. 
• You are a highly organized individual who truly believes in data driven decision making and is fanatical in terms of KPI measurement. Prior experience with OKRs and tying KPIs with OKRs.
• Strong interpersonal and teaming skills — this is an extremely collaborative environment.
• Prior SaaS, startup experience and experience working with a distributed team. Ability to work with some levels of ambiguity in terms of requirements.
• Exceptional written and verbal communication skills. 
• Worked with Agile development methodology and fluent with Git/Github (especially branching, merging, tagging).
• Bachelor’s degree in Computer Science, Engineering or related field, or equivalent training, fellowship, or work experience.

Nice-to-have skills & competencies:

• Experience with Data Technologies  and modern application stacks.
• Some knowledge of Machine Learning, NLP and Data Science in general.

What you will be doing:

• You will technically lead, motivate and grow SupportLogic’s UI engineering team.
• You will collaborate with product managers, UX designers, UI & backend engineers and Data Scientists to develop world-class UI architectures, implementations and experiences for our customers.
• You will execute and deliver on UI features with a bias for fast iteration and rapid feedback.
• You’ll engineer for usability, maintainability, reusabilityWe  (Atomic Design and Component based application development), testability (what can be automated should be) and performance. You will contribute to and enhance a culture of Engineering excellence fostering innovation and collaboration.
• You’ll define and implement our strategy for expanding to Mobile versions of the application. 
• Experiment and enable newer modes of interaction (Voice Assistants) for Enterprise applications.
• Provide meaningful and timely code reviews before merging pull requests.
• Constant learning is required and you will be reporting to the VP, Engineering

What you should have:

• Are located in the Bay Area and are a US Citizen (due to customer data access requirements)
• 10+ years of Software Engineering experience with at least 5+ years of experience in UI Development and at least 3+ years as a Lead UI Engineer delivering cloud-native, enterprise-grade, SaaS products.
• Prior startup experience and experience working with a distributed team. Exceptional written and verbal communication skills. Ability to work with some levels of ambiguity in terms of requirements.
• Strong UX design understanding and intuition with a proven history of shipping products with responsive and user-friendly UIs.
• Worked with AGILE development methodology and ceremonies and fluent with Git/Github.
• Demonstrated clear technical leadership and architecture skills. Familiarity with non-functional-requirements around Performance, Scalability, Security, Reusability (Component Based Implementation with Atomic Design flavors) and Testability (understanding of where automation works and does not with Frontend development).
• Proven experience with Benchmarking, Optimization and cross-browser concerns.
• Exceptionally strong in various technologies:
  • HTML/CSS
  • Javascript, Typescript and newer aspects of ECMAScript.
  • React (Deep understanding of React Architecture, Hooks, Workflows such as Flux/ Redux Thunk/Saga, DOM manipulation, reselect, react-query and other elements.
  •  Working knowledge of REST APIs (in Node.js and Python).
  • Knowledge of modern authorization such as OAuth2.0, JSON Web Token (JWT)
  • Familiarity with modern front-end build pipelines and tools such as Webpack, NPM and others..
  • Strong with CI/CD and Automation methodologies.
  • Strong culture of building reusable components and front-end libraries for reuse with a strong belief in unit testing prior to QA and integration testing. 
  • Familiarity with Mobile Development and the challenges of supporting user experiences across Web, Mobile and other interaction modalities.
• Bachelor’s degree in Computer Science, Engineering or related field, or equivalent training, fellowship, or work experience.
• You are self-starting, with the interest and passion to contribute in a fast-paced startup environment which encourages a “no-boundaries” attitude.

Nice-to-have skills & Competencies:

• Experience with Selenium and testing in headless mode scenarios on Jenkins.
• Experience with Angular.
• Experience with Voice integration (such as Alexa, Google Cloud speech-to-text etc.)

About SupportLogic

We are a well-funded startup with investments from top tier investors in Silicon Valley (Sorenson Ventures, Sierra Ventures). Privileged to have customers who are big fans of our product and proud of our 100% renewal rate with existing customers. We are a distributed team spread across the United States as well as internationally.

SupportLogic is building a new category of software that leverages natural language processing (NLP) and machine learning (ML) to empower businesses to improve their customer relationships, products, and operations. SupportLogic provides an abstraction layer for conventional ticketing systems (Systems of Record) such as SalesForce Service Cloud, Zendesk, JIRA, Dynamics and continuously analyzes the content of the ticketing system to provide intelligent recommendations and actionable insights in real-time.

Supportlogic has a positive, diverse, and supportive culture – we look for people who are curious, innovative, and strive for constant growth. In our work together we aim to be smart, humble, hardworking, respectful and above all, collaborative. You will be working in a fast-moving and growing company. Applicants should be self-starting and comfortable learning and using new software engineering methodologies, technologies, systems and processes.

About the UI Engineering Leader Role

The UI Engineering Leader position is an Individual Contributor role requiring proven leadership and team building success, a deep technical background, proficiency in UI architecture, full-stack design principles and development with clear communication, collaboration and relationship development skills. You love to delight customers with breathtakingly simple, user-friendly, effective UIs that solve their real world problems efficiently.

What you will be doing:

• You will technically lead, motivate and grow SupportLogic’s UI engineering team.
• You will collaborate with product managers, UX designers, UI & backend engineers and Data Scientists to develop world-class UI architectures, implementations and experiences for our customers.
• You will execute and deliver on UI features with a bias for fast iteration and rapid feedback.
• You’ll engineer for usability, maintainability, testability, reusability and performance. You will contribute to and enhance a culture of Engineering excellence fostering innovation and collaboration.
• Provide meaningful and timely code reviews before merging pull requests.
• Constant learning is required and you will be reporting to the VP, Engineering

What you should have:

• Are located in the Bay Area and are a US Citizen (due to customer data access requirements)
• 10+ years of Software Engineering experience with at least 5+ years of experience in UI Development and at least 3+ years as a Lead UI Engineer delivering SaaS products.
• Prior startup experience and experience working with a distributed team. Exceptional written and verbal communication skills. Ability to work with some levels of ambiguity in terms of requirements.
• Strong UX design understanding and intuition with a proven history of shipping products with responsive and user-friendly UIs.
• Worked with Agile development methodology and fluent with Git/Github.
• Demonstrated clear technical leadership and architecture skills. Familiarity with non-functional-requirements around Performance, Scalability, Security, Reusability and Testability.
• Proven experience with Benchmarking, Optimization and cross-browser concerns.
• Exceptionally strong in various technologies:
  ○ HTML/CSS
  ○ Javascript and newer aspects of ECMAScript.
  ○ React (Deep understanding of React Architecture, Hooks, Riot, Workflows such as Flux/ Redux, DOM manipulation, reselect, react-query and other elements)
  ○ Working knowledge of REST APIs (in Node.js and Python).
  ○ Knowledge of modern authorization such as JSON Web Token (JWT)
  ○ Familiarity with modern front-end build pipelines and tools such as Webpack, NPM and others..
  ○ Strong culture of building reusable components and front-end libraries for reuse with a strong belief in unit testing prior to QA and integration testing (via Mocha/Karma, Jasmine and/or other frameworks)
• Bachelor’s degree in Computer Science, Engineering or related field, or equivalent training, fellowship, or work experience.
• You are self-starting, with the interest and passion to contribute in a fast-paced startup environment which encourages a “no-boundaries” attitude.

Nice-to-have skills and competencies:

• Experience with Selenium and testing in headless mode scenarios.
• Experience with Angular.
• Familiarity with Mobile Development and the challenges of supporting user experiences across Web, Mobile and other interaction modalities.
• Experience with Voice integration (such as Alexa, Google Cloud speech-to-text etc.)

About SupportLogic

We are a well-funded startup with investments from top tier investors in Silicon Valley (Sorenson Ventures, Sierra Ventures). Privileged to have customers who are big fans of our product and proud of our 100% renewal rate with existing customers. We are a distributed team spread across the United States as well as internationally. 

SupportLogic is building a new category of software that leverages natural language processing (NLP) and machine learning (ML) to empower businesses to improve their customer relationships, products, and operations. SupportLogic provides an abstraction layer for conventional ticketing systems (Systems of Record) such as SalesForce Service Cloud, Zendesk, JIRA, Dynamics and continuously analyzes the content of the ticketing system to provide intelligent recommendations and actionable insights in real-time.

About the Data Science Team

The mission of the SupportLogic Data Science team is to create cutting-edge machine learning (ML) models that can extract new signals from unstructured data and make insightful, actionable predictions for our customers.

We are responsible for:

• Advancing the frontier of ML performance and Intellectual Property (IP) in order to maximize the value of SupportLogic to our customers
• Working with the Data Platform group to ensure ML models have a smooth path to production
• Working with the product design and UI teams to maximize the value of our predictions for our end users and customers

We are seeking a Machine Learning Engineer interested in working with data scientists and software engineers to ensure ML models are deployed into production efficiently, effectively, and with high confidence in customer-facing predictions.

You will be working in a fast-moving and growing company; applicants should be self-starting and comfortable learning and using new technologies, systems, and processes.

About the Machine Learning Engineer Role

Responsibilities:

• Deploy, monitor, and manage Machine Learning models
• Work with data scientists to provide high-quality ML model features efficiently in order to accelerate their research
• Work with data scientists to ensure ML model features are transferable to production environments, accelerating the path to production for new models
• Identify and rectify inefficiencies in data scientist workflows in order to accelerate model iteration and improvement
• Design and implement APIs or other means of gathering feedback to enable automated model iteration
• Harden and improve research-grade code into production-grade code before model deployment
• Design and implement APIs or other interfaces for model input/output in production
• Design and build test harnesses for ML models and/or APIs to ensure high-quality results before deploying new models to production
• Recommend ways to improve data reliability and quality and implement them if possible

Required skills and competencies:

• Located in the United States (due to customer data access requirements)
• 4+ years of professional software development experience
• 2+ years of experience as a full-time data scientist, data engineer, or machine learning engineer
• B.S., degree in Computer Science, Mathematics, or similar quantitative field of study
• Fluency in Python, and experience with common data science libraries, such as Pandas, numpy, and scikit-learn
• Experience working with machine learning models in a production and/or customer-facing environment
• Experience building APIs in Python, especially Flask and/or FastAPI
• Experience with docker in a professional environment
• Experience working on or with cloud platforms (AWS, GCP, Azure)
• Experience with SQL databases and SQL queries
• Self-starting, with the interest and passion to contribute in a fast-paced startup environment

Nice-to-have skills and competencies:

• M.S., in Computer Science, Mathematics, or similar quantitative field of study
• Prior startup experience
• Experience monitoring and measuring performance of machine learning models in a production environment

About SupportLogic

We are a well-funded startup with investments from top tier investors in Silicon Valley (Sorenson Ventures, Sierra Ventures). Privileged to have customers who are big fans of our product and proud of our 100% renewal rate with existing customers. We are a distributed team spread across the United States as well as internationally. 

SupportLogic is building a new category of software that leverages natural language processing (NLP) and machine learning (ML) to empower businesses to improve their customer relationships, products, and operations. SupportLogic provides an abstraction layer for conventional ticketing systems (Systems of Record) such as SalesForce Service Cloud, Zendesk, JIRA, Dynamics and continuously analyzes the content of the ticketing system to provide intelligent recommendations and actionable insights in real-time.

About the Data Science Team

The mission of the SupportLogic Data Science team is to create cutting-edge machine learning (ML) models that can extract new signals from unstructured data and make insightful, actionable predictions for our customers.

We are responsible for:

• Advancing the frontier of ML & NLP performance and Intellectual Property (IP) in order to maximize the value of SupportLogic to our customers
• Working with the Data Platform group to ensure ML models have a smooth path to production
• Working with the product design and UI teams to maximize the value of our predictions for our end users and customers

We are seeking a Senior Data Scientist with an interest in researching new ML and NLP models and techniques, researching and refining features, and evaluating model performance in both research and production environments.

You will be working in a fast-moving and growing company; applicants should be self-starting and comfortable learning and using new technologies, systems, and processes.

About the SeniorData Scientist Role

Responsibilities:

• Build, deploy, monitor, and manage Machine Learning models
• Identify valuable input features and implement a means for calculating them (feature engineering)
• Investigate, clean, analyze, and otherwise prepare new data sources for use in higher-order analysis or as input into model features
• Data analysis and presentation using data visualization techniques, sometimes to broader audiences within or outside of SupportLogic
• Transition models from research to production, working with Data Platform group as needed
• Fine-tune model performance in a production setting using adaptive/incremental machine learning techniques
• Map customer and/or product requirements to correct modeling, analysis, and/or visualization approaches
• Recommend ways to improve data reliability and quality and implement them

Required skills and competencies:

• Located in the United States (due to customer data access requirements)
• 10+ years of professional software development experience
• 5+ years of experience as a full-time data scientist, machine learning researcher, or machine learning engineer
• M.S., degree in Computer Science, Mathematics, or similar quantitative field of study
• Fluency in Python, and experience with common data science libraries, such as Pandas, numpy, and scikit-learn
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
• Experience with NLP (especially sentiment analysis, entity recognition, and use of the SpaCy library)
• Experience with SQL databases and SQL queries
• Self-starting, with the interest and passion to contribute in a fast-paced startup environment

Nice-to-have skills and competencies:

• Ph.D., in Computer Science, Mathematics, or similar quantitative field of study
• Prior startup experience
• Experience working on or with cloud platforms (AWS, GCP, Azure)
• Experience using neural networks and/or Deep Learning techniques and relevant Python platforms/APIs such as Tensorflow, PyTorch, and Keras in a production setting

The role:

This opportunity is excellent for someone looking for tremendous professional and personal growth. We are looking for an emotionally intelligent team-player with a highly positive attitude who is hungry to roll up their sleeves, drive revenue, learn, experiment, and grow within the company.

The work you’ll do:

• Work cross-functionally to develop, manage and execute integrated and account-based marketing programs and campaigns to drive lead engagement and sales pipeline.
• Manage and execute all aspects of planned activities from start to finish to meet deadlines and budget (including logistics, assets, and reporting).
• Continuously monitor, measure, and optimize campaigns and programs.
• Collaborate with product marketing, creative teams/agencies, and sales organizations to develop effective marketing assets to support campaign and program efforts.
• Align tactics (such as events, webinars, online advertising, content syndication, outbound emails, target account advertising, account-based marketing plays, etc) and content to the buyer’s journey.
• Proactively communicate plans and tactical details across executives, sales and marketing to build strong relationships and alignment.
• Design multi-variate testing strategies and execution across all channels.
• Co-design and expand lead management processes.

What you will bring to the role:

• Bachelor’s Degree in Business Administration/Marketing or related.
• 5 years of experience in B2B enterprise marketing.
• Excellent communication skills, both written and verbal. Ability to effectively present information to internal and external associates.
• Exceptional organizational and project management skills to manage multiple priorities in a fast-paced environment.
• Ability to take initiative and ownership with focus on continuous improvement.
• Experience with account-based marketing, demand generation strategies, digital marketing, and other marketing programs.
• Familiarity and experience with marketing automation systems (Pardot preferred), CRM (Salesforce.com preferred), webinar platforms (ON24 or Zoom), and CMS (wordpress preferred).
• Experience marketing SaaS and cloud-based solutions.

About SupportLogic

We are a well-funded startup with investments from top tier investors in Silicon Valley (Sorenson Ventures, Sierra Ventures). Privileged to have customers who are big fans of our product and proud of our 100% renewal rate with existing customers. We are a distributed team spread across the United States as well as internationally. 

SupportLogic is building a new category of software that leverages natural language processing (NLP) and machine learning (ML) to empower businesses to improve their customer relationships, products, and operations. SupportLogic provides an abstraction layer for conventional ticketing systems (Systems of Record) such as SalesForce Service Cloud, Zendesk, JIRA, Dynamics and continuously analyzes the content of the ticketing system to provide intelligent recommendations and actionable insights in real-time.

Location: Anywhere; San Francisco Bay Area preferred.

Responsibilities:

• Hands-on Product Owner who demonstrates an understanding of the Customer Success space and works with customers and prospects to define and prioritize new features and enhancements
• Internalize and represent the customers’ voice, create compelling user experiences, and define key product metrics to measure the success of features
• Work closely with UX designers, Engineering leaders and Customers to define user stories, providing feedback on suggested UI designs and requirements – own Product Design.
• Collaborate with Engineering leaders to do phased roll-outs of complex product features incorporating priority, quality and delivery trade-offs
• Product evangelist and thought leader at external forums, conferences, webinars and the Customer Advisory Board
• Be the liaison between Customers, Sales, Customer Success, Engineering and Marketing

Required skills and competencies:

• 5+ years of experience as a Technical Product Manager for an enterprise SaaS product
• Prior domain experience in Customer Support/Success
• Excellent presentation, collaboration and communication skills
• Strong product design intuition and creativity especially in the context of solving customer problems and user experience.
• Bachelor’s degree in Engineering, Computer Science or related field of study

Nice-to-have:

• Experience in Agile development methodologies
• MBA
• Prior domain experience in Data Analytics and Machine Learning

The ideal candidate must have a strong technical background (preferably as a software developer at some point), domain knowledge of Customer Success/Support, and experience as a Product Owner or Technical Product Manager in a SaaS Enterprise Software company. A passionate individual familiar with the challenges and aspects of building and operating cloud services at scale.  

About SupportLogic:

SupportLogic SX™ is a platform that elevates customer service experience by leveraging natural language processing (NLP) and machine learning (ML). The platform seamlessly integrates with your existing ticketing system (such as Salesforce Service Cloud, Zendesk, Microsoft Dynamics), reads all the comments in every ticket to extract key signals related to customer sentiment and churn, predicting outcomes and providing proactive recommendations.  Customer Support and Success organizations use the platform to stay on top of how their customers feel about them thus improving customer relationships, products and operations.

We are a well-funded startup with investments from top tier investors in Silicon Valley (Sorenson Ventures, Sierra Ventures) and a customer list that is a who’s-who of Enterprise IT companies.  We are privileged to have customers who are not only outspoken fans of our product but also prove it by renewing every year.