AI/ML Engineer - USA | Remote
About the Company
Commence delivers data-driven solutions, technology, and clinical expertise to improve health outcomes and make healthcare processes more efficient. Through human-centered, healthcare-focused, and value-based solutions, the company uses data to support better care and improve the lives of the people it serves. Its approach is built on straightforward communication, clinical domain expertise, and a focus on measurable results.
About the Role
Commence is seeking an AI/ML Engineer to build, train, and validate machine learning models that support clinical and operational data products across the healthcare ecosystem. The role also contributes to bringing models into production, including supporting document processing pipelines and AI/LLM-driven workflows. The ideal candidate has practical machine learning experience, understands healthcare datasets such as EHRs, claims, and FHIR, and can independently manage well-defined model development assignments. The engineer will work within established technical frameworks and collaborate with senior engineers on system design, architecture, and compliance decisions.
Key Responsibilities
Build, train, and validate machine learning models, including data ingestion, feature engineering, and model evaluation, based on requirements from Senior Engineers or Data Scientists. Contribute to deploying machine learning and AI models into APIs, batch processes, and streaming workflows under the guidance of Senior AI/ML Engineers. Support AI/LLM-driven workflows for document extraction, classification, and summarization using established frameworks and orchestration patterns. Assist with implementing Retrieval-Augmented Generation (RAG) components, embedding strategies, and vector-based retrieval within existing architecture. Apply established MLOps practices, including CI/CD pipelines, model versioning, and retraining workflows. Use Databricks tools, including Workflows, Delta Lake, and Unity Catalog, along with AWS services such as S3, Lambda, and Bedrock, to support model training and inference. Monitor deployed model performance, including latency, throughput, and accuracy drift, and troubleshoot issues while escalating architecture-level concerns to Senior Engineers. Maintain existing monitoring, alerting, and observability tools for assigned models. Collaborate with Data Engineers, Data Scientists, and Software Engineers to deliver components of larger AI/ML systems. Follow established practices to support compliance 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 information. Stay informed about emerging AI/ML tools and techniques and bring relevant options to the team for evaluation. Document model development, testing, and validation activities to support reproducibility and audit readiness.
Required Qualifications
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field. 3–5 years of experience in machine learning engineering, data science, or software engineering. Strong proficiency in Python and SQL, with experience building production-grade systems. Practical experience with machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch. Experience deploying machine learning models in production environments through batch or API-based workflows, with senior engineering support for system design. Exposure to AI/LLM platforms such as AWS Bedrock, Anthropic, LangChain, or Databricks Agent frameworks. Familiarity with distributed data processing frameworks such as PySpark, Databricks, or AWS EMR. Experience with machine learning lifecycle tools such as MLflow, model registries, and monitoring frameworks. Experience building APIs or services for model inference using tools such as FastAPI or Flask. Solid understanding of software engineering principles and their application to machine learning workflows. Experience working with healthcare datasets such as EHRs, claims, FHIR, or HL7. Strong problem-solving skills and attention to detail. Effective communication and collaboration skills when working with technical and non-technical teams.
Preferred Qualifications
Exposure to vector databases, embeddings, or RAG components. Experience with OCR and document AI tools such as AWS Textract or DBX OCR. Experience with containerization and orchestration tools such as Docker and Kubernetes. Familiarity with healthcare data governance and security frameworks such as NIST or HITRUST. Experience supporting federal healthcare programs or agencies, including CMS, VA, or DoD. Knowledge of healthcare delivery systems, quality measurement programs, or policy frameworks. Work Environment and Physical Requirements This is a remote position. Employees regularly work in a climate-controlled environment and must be able to sit, read, use a computer, and view a computer screen for extended periods. Occasional physical activities may include standing, walking, using hands and fingers, kneeling, or crouching. Reasonable accommodations may be provided to enable individuals with disabilities to perform the essential functions of the role. Equal Employment Opportunity Commence is an equal employment opportunity employer. All personnel processes are merit-based and conducted without discrimination based on race, color, religion, sex, sexual orientation, gender identity, marital status, age, disability, national or ethnic origin, military or veteran status, or any other characteristic protected by applicable law. Commence is committed to providing equal employment opportunities to all applicants, including individuals with disabilities. Applicants who require a reasonable accommodation during the application process may contact Human Resources at (757) 306-4920 or [email protected]. Application Process Unless requesting a reasonable accommodation, applicants must submit all applications through the online application system.