Job Description

Our client is a profitable, San Diego based and mission-driven HealthTech company that recently raised strategic funding to accelerate growth. Their platform provides services to school districts, children, families, and municipalities to access critical mental health and behavioral health support.

We are actively seeking a talented and creative Staff Machine Learning Engineer to lead key initiatives from the ground up: building applied ML systems, setting infrastructure foundations, and shaping the future of behavioral health access.

This is a rare opportunity to build applied ML systems from the ground up, in a startup-like environment but with the stability of a highly profitable and established organization. Your work won’t be abstract: it will directly impact how students, families, and communities get matched with life-changing wellness support.

Duties Include:

• Lead the development and deployment of core ML models (recommender systems, classification, personalization)
• Design and implement production pipelines, monitoring systems, and infrastructure to support ML at scale
• Integrate ML models into a Django-based backend using both batch and real-time methods
• Partner on the design of an ML Gateway to connect models cleanly to production systems
• Collaborate closely with NLP and data engineering teams to define schemas, feedback loops, and standards
• Establish best practices for model versioning, observability, and operational efficiency
• Help set technical strategy while mentoring others and contributing to team culture

Projects You’ll Tackle:

• Intelligent provider matching using multiple signals (clinical fit, availability, insurance, geography)
• Building vector-based semantic search for better results, especially for non-technical users
• Creating robust ML infrastructure for a mission-critical, regulated environment
• Collaborating on NLP models that classify and route free-text inputs for faster triage
• Partnering on LLM-enabled tools for care coordination and support

Required Experience:

• 7+ years of current experience building and shipping ML systems in commercial, product-focused companies
• 3+ years as Senior IC or Lead Engineer, owning end-to-end ML projects (e.g., recommender systems, classification, personalization)
• Strong, hands-on Python and backend integration experience (e.g., batch, APIs), bonus if with Django
• Track record with model monitoring, deployment, and tools like MLflow, Airflow
• Solid grasp of systems design and engineering best practices
• Work Location: Remote-friendly, but San Diego-based candidates strongly preferred. Team meets in person 2–3 days per week.
• Required: Must be authorized to work in the U.S. without current or future visa sponsorship.

Bonus Experience:

• Semantic search, vector embeddings, or LLMs
• Healthcare, mental health, or other mission-driven domains
• AWS-native ML infrastructure, Kubernetes, Docker

COMPENSATION: $180K – $220K base salary

• BENEFITS : Excellent comprehensive healthcare and wellness benefits, 401K, pre-IPO equity, and potential for relocation package to move to San Diego

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