Note: The job is a remote job and is open to candidates in USA. ELLKAY is a trusted data management partner in healthcare, providing innovative solutions for interoperability and data management. They are seeking a staff-level machine learning engineer to design, integrate, and operate AI-powered systems across various platforms and products, ensuring reliable end-to-end solutions in production settings.
Responsibilities
- Design and implement AI-enabled workflows that span internal platforms, third-party systems, APIs, databases, and operational tools
- Build integration pipelines for ingestion, transformation, model inference, decisioning, and downstream actions in batch and real-time environments
- Architect reusable system components such as connectors, transformation layers, orchestration patterns, and event-driven services that make AI capabilities easier to deploy across the organization
- Develop production services and APIs that expose AI functionality safely and reliably to enterprise applications and users
- Partner with product, infrastructure, and data teams to operationalize ML and LLM capabilities in business-critical workflows
- Establish engineering standards for reliability, observability, versioning, testing, evaluation, and governance of AI systems in production
- Mentor engineers and help shape the technical roadmap for AI systems integration and platform architecture
- Build systems that work with healthcare interoperability standards such as FHIR R4, HL7 v2, and USCDI data elements
- Integrate clinical terminologies and ontology services including LOINC, SNOMED, and RxNorm to support normalization, retrieval, and decision support workflows
- Design solutions that protect PHI and align with HIPAA and broader security requirements for regulated environments
- Build high-performance backend services using modern Python frameworks such as FastAPI and Pydantic, with strong error handling, retry logic, and asynchronous execution patterns
- Design cloud-native architectures using services such as AWS Lambda, API Gateway, Step Functions, EventBridge, SQS, SNS, ECS Fargate, Aurora PostgreSQL, DynamoDB, and S3
- Write production-grade infrastructure as code using AWS CDK in Python or TypeScript, including support for multi-tenant deployments and cross-account environments
- Implement secure and observable systems using structured logging, distributed tracing, metrics, alarms, encryption, secrets management, and least-privilege access controls
- Design rigorous evaluation frameworks for ML and AI systems, including benchmark creation, held-out test sets, label-quality controls, leakage prevention, and model comparison methods
- Implement prompt versioning, controlled experiments, and A/B testing approaches to continuously improve model and workflow performance
- Drive strong engineering discipline in code quality, testing, deployment hygiene, and production support
Skills
- 10+ years of experience in software engineering, machine learning engineering, or closely related fields, including meaningful ownership of production systems
- Strong grounding in machine learning fundamentals, including model development, evaluation, deployment, and performance trade-offs
- Proven experience building distributed systems, integration platforms, or complex workflow-driven applications
- Expertise designing workflows across heterogeneous systems, including APIs, event streams, databases, and enterprise applications
- Strong programming ability in Python and working knowledge of Java or Go
- Experience with orchestration frameworks such as Airflow, Temporal, or Prefect
- Experience with messaging and streaming systems such as Kafka or Pub/Sub
- Experience designing and operating REST or gRPC APIs and data transformation pipelines
- Familiarity with modern AI application patterns, including LLMs, retrieval systems, vector databases, and model-integrated application workflows
- Strong communication skills and the ability to collaborate effectively across product, platform, security, and data teams
- Experience building or extending integration engines or middleware platforms similar to Iguana, MuleSoft, or Apache Camel
- Experience in healthcare or another regulated industry with complex data movement, auditability, and compliance needs
- Experience with event-driven architectures and real-time processing systems at scale
- Familiarity with Amazon Bedrock, Claude family models, or comparable enterprise AI platforms
- Contributions to open-source software, interoperability initiatives, or internal developer platforms
- Degree in computer science, machine learning, or a related technical field
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
- Professional growth within
- Innovation environment
- On site in HQ Free daily lunches
- Our awesome culture includes: Working with talented, collaborative, and friendly people who love what they do
- ELLKAY is committed to operating as a 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, we are open to considering remote work for candidates whose skills and experience strongly align with the role
Company Overview
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