Onos Health

Compensation

Full Description

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 healthcare data 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 outcomes while making healthcare more affordable. Onos recently closed a $6M Seed round with top-tier investors and is already working with some of the nation’s largest health plans, signing its first national plan just months after launch. 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 and highly capable AI/ML engineer who is motivated to meaningfully improve the way healthcare is administered in the United States. You'll take ownership of developing a significant part of the Onos platform, including the development of models for assessing the level of appropriate care for patients. As an early team member, you'll be expected to wear multiple hats, including acting as a backend/data engineer, while ensuring excellent outcomes for our 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: Design, develop and deploy sophisticated ML models to analyze healthcare data and detect anomalies, classify patients according to level-of-care guidelines, and make accurate recommendations Develop LLM/NLU systems to process and extract meaningful information from clinical notes and medical documents Build data pipelines that scale efficiently while maintaining strict data privacy and security standards Establish machine learning & AI best practices, evaluation frameworks, and model governance for future team growth Collaborate with backend engineers to integrate AI/ML capabilities seamlessly into the Onos platform Technical Challenges At Onos: Build AI/ML pipelines to analyze medical records to streamline clinical assessments and healthcare quality reviews Design explainable AI solutions that provide transparency into model decisions for healthcare professionals Develop an intelligent engine that ingests complex medical standards of care documents and evaluates provider adherence to guidelines Create robust anomaly detection algorithms to identify patterns of fraud, waste, and abuse in healthcare claims 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: 5+ years experience building and deploying machine learning systems in production Significant experience working with data pipelines and Python and related data science/ML libraries Experience with developing LLM-based systems and integrating them with user-facing features Deep understanding of the limitations of using LLMs and the best practices for using them for reliable, consistent, and accurate outputs Customer obsessed and motivated to make an impact in the healthcare space A collaborative team player with a focus on delivering measurable results Bonus points if you have: Experience wearing multiple hats as a generalist backend engineer Significant experience working with healthcare data and with HIPAA best practices Experience with explainable AI and model governance in regulated industries Led teams of ML engineers or data scientists on major projects Knowledge of modern ML infrastructure and MLOps best practices Built and deployed large language models for production applications Benefits and Perks Flexible hybrid arrangement: 2-3 days/week at San Francisco office (Financial District), remote-first culture Unlimited vacation policy Paid parental leave Medical, dental, and vision insurance Pre-tax commuter benefits 401(k) Significant equity as an early employee Direct mentorship from experienced founders Ground-floor opportunity to help build a team and culture Regular team events and offsites Company-provided equipment and home office setup We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.