Note: The job is a remote job and is open to candidates in USA. ELLKAY is hiring a Staff ML Engineer to lead the design and delivery of shared AI/ML services across its migration, archive, connector, and interoperability products. The role develops models and governed LLM agents, establishes reusable serving interfaces and engineering standards, and mentors the ML team while partnering with platform, product, clinical, and security leaders to bring pilots into production.
Responsibilities
- Define the shared AI architecture, model-routing approach, retrieval interfaces, tool contracts, and release criteria. Lead design reviews and mentor the distributed ML team
- Design governed agent experiences for implementation guidance, migration recommendations, operational explanations, and archive retrieval
- Integrate with the shared agent gateway and existing platform APIs. Enforce tenant and purpose checks, approvals for actions, async job status, and auditable tool execution
- Choose between rules, classical ML, retrieval, and LLMs using measured quality, latency, and cost. Coordinate rollout from synthetic sandbox to approved customer pilots
- Develop reference implementations and own difficult production failures, including model regressions, retrieval errors, invalid tool actions, and latency/cost overruns
Skills
- 8+ years of relevant software/ML engineering experience, with ownership of production ML systems and technical leadership across teams
- Strong Python and SQL, sound software design, automated testing, API development, and experience with PyTorch, scikit-learn, or comparable ML frameworks
- Hands-on model training, feature engineering, model selection, error analysis, statistical evaluation, and techniques to prevent dataset leakage
- Production experience with LLM applications, retrieval-augmented generation, embeddings, tool calling, model routing, and structured outputs
- Ability to design distributed services, cloud serving, access controls, model/prompt lifecycle management, and cost/performance tradeoffs
- Evidence of mentoring engineers and translating product needs into deliverable technical designs
- A relevant degree or equivalent practical experience is acceptable
- Healthcare integration or regulated enterprise AI
- MCP/tool-calling experience
- AWS and Snowflake
- Familiarity with HL7, FHIR, and migration or archive workflows
- Framework experience such as LangGraph or an equivalent orchestration approach is useful
Benefits
- Medical, Dental, and Vision benefits
- Employer-paid Life and LTD
- 401k w/ matching – once eligibility is met
- Work/life balance
- Paid Volunteer Program
- Flexible working hours
- Generous FTO
- Remote work options
- Employee Discounts
- Parental Leave
- Gym membership / Exercise class stipends
- Working with talented, collaborative, and friendly people who love what they do
- Professional growth within
- Innovation environment
- On site in HQ Free daily lunches
- Hybrid workplace, offering employees flexibility in how they structure their time between in-office and remote work
- For those who do not live within 40 miles of one of our offices, remote work may be considered for candidates whose skills and experience strongly align with the role
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