Lead AI/ML Engineer-Remote Nationwide or Hybrid in MN/DC
About The Position
Our Value Connect team is building an AI-first platform for value-based care that uses ML, LLMs, agents, and automation to improve provider performance, care outcomes, cost management, and operational efficiency. The team is developing capabilities such as Predictive Models, conversational AI assistants, Agentic workflows, MLOps, Registry automation, Ambient listening etc. The Lead AI/ML Engineer will provide hands-on technical leadership to build scalable, production-ready AI/ML solutions that convert complex healthcare data into actionable workflows for care, quality, finance, and provider enablement teams. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.
Requirements
- Bachelor’s degree with 6+ years, or Master’s with 4+ years, or PhD with 3+ years of relevant experience in AI/ML engineering or related fields
- 3+ years of hands-on experience building, validating, tuning, and evaluating classical ML, deep learning, and Generative AI models
- 3+ years of professional experience writing production-grade code in Python and utilizing modern ML/AI libraries
- 2+ years of experience building and deploying AI systems utilizing RAG frameworks, vector databases, or orchestration libraries (e.g., LangChain, LangGraph)
- Experience deploying, operating, and managing MLOps workloads on cloud platforms (Azure, AWS) utilizing containerization
- Experience applying core software engineering practices, including version control (GitHub), code reviews, and CI/CD pipelines
Nice To Haves
- Experience in healthcare technology, clinical data processing, or value-based care platforms
- Experience with distributed computing technologies (e.g., Spark, Databricks)
- Experience with model optimization techniques such as quantization, fine-tuning, and model compression
- Proven ability to translate complex business requirements into scalable technical solutions and communicate them to non-technical stakeholders
Responsibilities
- Lead the design, architecture, and end-to-end implementation of AI/ML, GenAI, RAG-based, and agentic solutions
- Apply machine learning, deep learning, statistical, and Generative AI techniques to solve complex clinical, operational, and financial business problems
- Build, validate, optimize, and tune AI/ML models, including fine-tuning, quantization, performance tuning, and cost optimization
- Develop and maintain production-grade APIs, such as FastAPI or REST services, to expose AI capabilities at scale
- Own MLOps practices, including model versioning, lifecycle management, CI/CD, monitoring, logging, drift detection, and reliability
- Deploy and operate AI workloads on cloud platforms such as Azure or AWS using containerization, Databricks, PySpark, and modern data platforms
- Establish engineering best practices for software quality, testing, security, responsible AI, design reviews, and code reviews
- Partner with product, data science, clinical, and business stakeholders while mentoring engineers and evaluating emerging AI technologies
- Leverage enterprise-approved AI tools and technologies to streamline developer workflows, automate tasks, and drive continuous improvement across the platform
Benefits
- comprehensive benefits package
- incentive and recognition programs
- equity stock purchase
- 401k contribution
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What This Job Offers
Job Type
Full-time
Career Level
Senior
