AI/ML Engineer

Description At Commence, we’re 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.? Requirements The AI/ML Engineer builds, trains, and validates machine learning models that power clinical and operational data products across the healthcare ecosystem, and contributes hands-on to productionizing those models, including supporting document processing pipelines and AI/LLM-driven workflows. The ideal candidate has solid hands-on ML experience, is comfortable working with healthcare datasets (EHRs, claims, FHIR), and can independently own well-scoped model development work while relying on senior engineers for system design, compliance, and architecture decisions. Build, train, and validate machine learning models, including data ingestion, feature engineering, and model evaluation, against requirements defined by Senior Engineers or Data Scientists. Contribute to productionizing machine learning and AI models into APIs, batch, and streaming workflows, under the direction of Senior AI/ML Engineers. Support development of AI/LLM-driven workflows (e.g., document extraction, classification, summarization) using frameworks and orchestration patterns established by senior technical staff. Assist in implementing Retrieval-Augmented Generation (RAG) components, embedding strategies, and vector-based retrieval within architecture designed by senior engineers. Apply established MLOps practices, including CI/CD pipelines, model versioning, and retraining workflows, within existing team standards. Work within Databricks (Workflows, Delta Lake, Unity Catalog) and AWS services (S3, Lambda, Bedrock) to support model training and inference tasks. Monitor deployed model performance (latency, throughput, accuracy drift) and troubleshoot issues, escalating architecture-level problems to Senior Engineers. Use and maintain existing monitoring, alerting, and observability tooling for models the engineer owns. Collaborate with Data Engineers, Data Scientists, and Software Engineers to deliver assigned components of larger AI/ML systems. Follow established practices to keep AI/ML work compliant 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. Stay current on emerging AI/ML tools and techniques and bring relevant options to the team for evaluation. Document model development, testing, and validation work to support reproducibility and audit readiness. 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 programming languages such as Python and SQL, with experience building production-grade systems. Practical experience with ML libraries such as Scikit-learn, TensorFlow, or PyTorch. Experience deploying machine learning models to production environments (batch or API-based), with support from senior engineers on 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 ML lifecycle tools such as MLflow, model registries, and monitoring frameworks. Experience building APIs or services (e.g., FastAPI, Flask) for model inference. Solid understanding of software engineering principles and their application to ML workflows. 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 Qualifications Exposure to vector databases, embeddings, or RAG components. 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 a remote 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 merit-based and 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. Commence is committed to providing equal employment opportunities to all applicants, including individuals with disabilities. If you require a reasonable accommodation to participate in the application process due to a disability, please contact Human Resources at (757) 306-4920 or [email protected]. Please note that unless you are requesting an accommodation, all applications must be submitted through our online application system.