Note: The job is a remote job and is open to candidates in USA. Commence develops data-driven healthcare solutions that combine technology, clinical expertise, and quality data to improve care and operational efficiency. The Senior AI/ML Engineer will design, build, and operationalize scalable machine learning and AI systems, including LLM, document processing, predictive, and MLOps solutions, while partnering with data and product teams in a secure and compliant healthcare environment.
Responsibilities
- Design, build, and maintain end-to-end machine learning pipelines, including data ingestion, feature engineering, model training, validation, deployment, and monitoring
- Productionize machine learning and AI models developed by Data Scientists into scalable APIs, batch, and streaming workflows
- Develop and optimize AI/LLM-driven workflows (e.g., document extraction, classification, summarization) using modern frameworks and orchestration patterns
- Implement Retrieval-Augmented Generation (RAG) pipelines, embedding strategies, and vector-based retrieval systems
- Establish and maintain MLOps practices, including CI/CD pipelines, model versioning, lineage tracking, and automated retraining workflows
- Integrate AI/ML systems within Databricks (Workflows, Delta Lake, Unity Catalog) and AWS services (S3, Lambda, Bedrock)
- Optimize model inference performance, latency, throughput, and cost efficiency across production systems
- Design and implement monitoring, alerting, and observability frameworks for deployed AI/ML systems
- Collaborate with Data Engineers, Data Scientists, and Software Engineers to define system requirements and deliver scalable AI solutions
- Ensure AI/ML systems comply with HIPAA, 42 CFR Part 2, FedRAMP Moderate, and other applicable regulatory frameworks
- Implement secure data handling practices, including encryption, access controls, and protection of sensitive healthcare data
- Evaluate and adopt emerging AI/ML technologies, tools, and frameworks to improve system capabilities and performance
- Mentor junior and mid-level engineers in best practices related to ML engineering, system design, and production AI systems
Skills
- Bachelor's degree in Computer Science, Engineering, or a related field
- 6+ years of experience in machine learning engineering, software engineering, or related roles
- Strong proficiency in programming languages such as Python and SQL, with experience building production-grade systems
- Demonstrated experience deploying and managing machine learning models in production environments
- Experience implementing AI/LLM solutions using platforms such as AWS Bedrock, Anthropic, LangChain, Databricks Agent frameworks, or similar
- Experience with distributed data processing frameworks such as PySpark, Databricks, or AWS EMR
- Experience with ML lifecycle tools such as MLflow, model registries, and monitoring frameworks
- Experience building APIs or services (e.g., FastAPI, Flask) for model inference
- Strong understanding of software engineering principles, system design, and scalable architecture
- Experience working with healthcare datasets such as EHRs, claims, FHIR, or HL7
- Strong problem-solving skills and attention to detail
- Strong communication and collaboration skills across technical and non-technical teams
- Candidates must be able to sit, read, work on a computer, and watch a computer screen for extended periods
- Occasionally required to stand, walk, use hands and fingers, kneel or crouch
- Master's degree
- Experience with vector databases, embeddings, and RAG architectures
- Experience with OCR/document AI tools (e.g., AWS Textract, DBX OCR)
- Experience with containerization and orchestration (Docker, Kubernetes)
- Familiarity with healthcare data governance and security frameworks such as NIST or HITRUST
- Experience supporting federal healthcare programs or agencies such as CMS, VA, or DoD
- Knowledge of healthcare delivery systems, quality measurement programs, or policy frameworks
Benefits
- This is an office/remote position.
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