Sr. AIML Engineer

At Commence were the start of a new age of data-centric transformation elevating health outcomes and powering better more efficient process to program and patient health. We combine quality data-driven solutions that fuel answers technology that advances performance and clinical expertise that builds trust to create a more efficient path to quality care.

With human-centered healthcare-relevant and value-based solutions we create new possibilities with data. We provide proof beyond the concept and performance beyond the scope with a focus on efficiencies that transform the lives of those we serve. With a culture driven by purpose straightforward communication and clinical domain expertise Commence cuts straight to better care.

The Senior AI/ML Engineer is responsible for designing building and operationalizing scalable machine learning and AI systems that power clinical and operational data products across the healthcare ecosystem. This role focuses on productionizing AI/ML capabilities including large language models (LLMs) document processing pipelines and predictive systems within a secure and compliant environment.

You will partner closely with Data Scientists Data Engineers and Product teams to transform models and prototypes into reliable performant and production-grade systems. The ideal candidate has strong data science and MLOps experience is comfortable working with complex healthcare datasets (EHRs claims FHIR) and can build scalable AI solutions that meet regulatory and operational requirements.

• 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.

Qualifications

• Bachelors degree in Computer Science Engineering or a related field. Masters degree preferred.
• 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.

Preferred Requirements

• 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.

Work Environment/Physical Demands

The work environment and physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

This is an office position. While performing the duties of this job the employee regularly works in a climate-controlled environment. Candidates must be able to sit read work on a computer and watch a computer screen for extended periods of time. Occasionally required to stand walk use hands and fingers kneel or crouch.

Commence is an equal employment opportunity employer. All personnel processes are applied without discrimination on the basis of race color religion sex sexual orientation gender identity marital status age disability national or ethnic origin military and veteran status or any other characteristic protected by applicable law. If you require a reasonable accommodation to participate in the application process due to a disability please contact Human Resources at or

Please note that unless you are requesting an accommodation all applications must be submitted through our online application system.