- Company Name
- Trillium Health Partners
- Job Title
- Senior ML Engineer
- Job Description
-
**Job Title:** Senior Machine Learning Engineer
**Role Summary:**
Lead the design, development, and operationalization of advanced AI solutions—including intelligent agents, agentic AI, and predictive models—for a large health‑care organization. Drive end‑to‑end AI product lifecycles, collaborate with clinical, operational, and technology teams, and ensure AI integration aligns with user‑experience, safety, and compliance standards.
**Expectations:**
- Deliver scalable, production‑grade AI systems that improve clinical and operational workflows.
- Partner cross‑functionally (IT, Business Intelligence, clinical units) to identify automation opportunities and embed AI into daily processes.
- Maintain high reliability, security, and ethical standards for AI outputs in a healthcare environment.
- Communicate technical concepts to non‑technical stakeholders and mentor junior engineers.
**Key Responsibilities:**
- Architect and build intelligent agents using platforms such as Microsoft Copilot Studio, Azure AI Foundry, Claude Skills, and Google Gemini.
- Develop, test, and deploy machine‑learning models and AI agents, managing the full product lifecycle from prototype to sustained production.
- Design and implement data pipelines for large, complex health‑care datasets, including validation, transformation, and feature engineering.
- Create and expose API endpoints and Model Context Protocols (MCPs) for secure exchange of healthcare information.
- Integrate AI agents with core hospital systems (EHR, HRIS, ERP) via APIs to enable actionable interactions.
- Craft system prompts and response frameworks that ensure safe, empathetic, and compliant AI behavior.
- Monitor production performance, troubleshoot issues, and implement continuous improvement processes.
- Lead AI integration initiatives across the enterprise and with external partners.
**Required Skills:**
- Strong object‑oriented design and software engineering fundamentals.
- Expert‑level programming in Python; comfortable with modern ML libraries and frameworks.
- Experience designing and operating large‑scale AI/ML platforms and services.
- Proficiency with cloud AI tools (e.g., Azure AI, Google AI, Microsoft Copilot) and containerization/orchestration (Docker, Kubernetes).
- Solid understanding of data engineering, ETL processes, and feature store concepts.
- Ability to develop secure RESTful APIs and implement integration protocols.
- Knowledge of healthcare data standards (FHIR, HL7) and regulatory considerations a plus.
- Strong problem‑solving, communication, and teamwork skills.
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Data Science, or a related technical discipline.
- Relevant certifications (e.g., Azure AI Engineer Associate, Google Cloud Professional Machine Learning Engineer, AWS Certified Machine Learning – Specialty) are advantageous but not mandatory.