Job Opportunities API

ABOUT ONOS HEALTH Onos Health’s mission is simple but ambitious: ensure every healthcare dollar goes toward delivering the highest quality care. Today, 30% of total U.S. healthcare spending is wasted due to ineffective care and administrative burden caused by misalignment between providers and payers. Onos is addressing this by building the largest AI-driven behavioral healthcare platform. Our models enables payers to make faster, more accurate decisions across their populations. By guiding members to the right care, Onos is channeling more dollars to high-quality care that drives better outcomes while making healthcare more affordable. Onos is well-funded by some of the best healthcare investors and is working with the nation’s largest health plans. Come join a category-defining company and help reimagine healthcare for the better. WHY ONOS? - Meaningful impact: Help fix what is fundamentally broken in healthcare - Direct collaboration: Work alongside experienced founders with deep healthcare and data expertise - Culture: Join a high-performing, transparent, and results-oriented team - Ownership: Significant responsibility and autonomy from day one - Opportunity: Play a pivotal role in building a fast-growing, category-defining healthcare AI company THE ROLE We're seeking an experienced AI/ML engineer who is motivated to meaningfully improve the way healthcare is administered in the United States. You'll be responsible for making the core Onos Health AI extraction and evaluation systems accurate, consistent, and trustworthy enough for health plans to depend on. As an early team member, you'll be expected to wear multiple hats and ensure excellent outcomes for our enterprise customers. This role is a hybrid role based in San Francisco, where you'll be expected to work at our office in person 2-3 times a week. WHAT YOU'LL BE DOING AT ONOS: - Develop LLM/NLU systems to process and extract meaningful information from clinical notes and medical documents, classify patients according to level-of-care guidelines, and make accurate recommendations - Own and evolve our LLM evaluation harness, regression gates, and observability to ensure our systems catch accuracy regressions before they reach payers and prove the platform's reliability over time - Extract structured data from visually complex clinical documents, including scanned charts, tables, and graphs using a mix of OCR, multimodal models, and classical ML - Collaborate with backend engineers to integrate AI/ML capabilities seamlessly into the Onos platform TECHNICAL CHALLENGES AT ONOS: - Build and operationalize AI/data pipelines to analyze medical records to streamline clinical assessments and healthcare quality reviews - Benchmark and stress-test LLM systems so evidence extraction and level-of-care classification stay accurate and reliable as criteria, documents, and models change - Develop and optimize a system that ingests complex medical standards of care documents and evaluates provider adherence to guidelines - Design explainable AI solutions that provide transparency into model decisions for healthcare professionals Tech Stack: - Infrastructure/Systems: AWS (ECS, Bedrock, Cognito, etc.), Docker, Github Actions - Languages/Frameworks: Python, Django, Celery, django-ninja, django-tenants - Database/Storage: PostgreSQL (AWS RDS), S3 - Development Tools: Github, Jira, CoderabbitAI, Tusk, Claude WHAT WE'RE LOOKING FOR: - 4+ years experience building and deploying applications in production in a backend engineering / data engineering capacity - Relevant experience with developing LLM-based systems for ingesting and evaluating unstructured records for industry-specific use cases and integrating them with user-facing features - Experience with document AI, OCR, or extracting data from visual/scanned content (charts, graphs, tables) - Deep understanding of the limitations of using LLMs and the best practices