Staff Software Engineer (AI/ML)
Onos Health
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.
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