Machine Learning Engineering Team Lead

Navina is a fast-growing digital health SaaS company that’s on a mission to transform the way physicians interact with patient data. Thousands of clinicians across the United States already use Navina’s AI-powered solution that transforms complex and fragmented patient data into concise “patient portraits" and actionable clinical insights at the point of care. With Navina, physicians experience less burnout, reduce missed diagnoses, and can devote more time giving better care to their patients.

Navina has been named one of the Top 100 AI companies globally by CB Insights and made the list of the Top 50 Digital Health startups. We are already working with industry-leading value-based organizations including Privia Health and Agilon.

We are looking for an experienced MLE Team Lead to lead our Machine Learning Engineering team as part of the Infrastructure group. AI/ML are core components of Navina unique technology, and a significant part of our technical edge. This is a unique opportunity to take a leadership role in building the infrastructure that powers the models driving Navina’s products.

You’ll lead a team of ML engineers in designing scalable production systems, collaborating with cross-functional stakeholders, and mentoring team members as we scale our ML platform and capabilities.

Requirements:

5+ years of hands-on experience in software engineering, with at least 2 years in a managerial role.
Experience leading technical teams and delivering complex projects, from concept to production.
Strong background in building systems to support production machine learning workflows.
Proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or similar.
Experience with large scale, high performance, production environments.
Strong interpersonal and communication skills, with experience collaborating across teams.
Experience in a cloud environment (preferably AWS).
Bs.c / Ms.c in Computer Science / Software Engineering.

Advantages:

Experience with Deep Learning, NLP and LLM pipelines (RAG and agentic systems).

You don’t need to meet 100% of the requirements to be a great fit. We believe in hiring people, not just checklists, and we value potential as much as experience. If this role excites you, we’d love to see your application!

Responsibilities:

Provide technical leadership and team management for the Machine Learning Engineering team, including mentoring team members, and encourage ongoing personal and professional growth.
Define and drive the roadmap for ML infrastructure in collaboration with other technical leaders and data science team, ensuring alignment with broader engineering and organizational goals.
Remain actively involved in the architecture and development of systems that enable scalable and reliable model training, deployment, serving, and monitoring.
Own the engineering aspects of the ML lifecycle, including the design of efficient production-grade deployment mechanisms, robust observability and maintenance practices.
Work closely with data science, product, medical, and dev teams to understand evolving needs and deliver infrastructure and tooling that improve development velocity and model reliability.
Continuously evaluate emerging tools and best practices in ML infrastructure and thoughtfully integrate relevant technologies to strengthen the team’s capabilities.