Lead Engineer (Machine Learning)

About Onos Health

Onos Health's mission is ambitious - ensure every healthcare dollar is spent on delivering the highest quality care. With up to 50 cents of every healthcare dollar wasted, Onos' AI-powered platform is positioned to drive meaningful change in the industry.

Onos empowers health plans to ensure their members receive the highest quality care while reducing billions in wasteful and abusive spending. By identifying providers who deviate from an evidence-based care standard, we enable health plans to take action before their members' health outcomes are impacted.

As one of our early engineering hires reporting directly to the CTO, you'll have the opportunity to shape our technical foundation from the ground up. You'll help to build sophisticated AI/ML systems that directly impact mental healthcare delivery while working alongside a team with decades of behavioral health experience.

Why Onos?

• Meaningful impact: Help improve the quality of care while reducing healthcare costs
• Direct collaboration with experienced founders who have deep healthcare expertise
• Collaborative, transparent & results-oriented culture
• Significant ownership of technical decisions and architecture from day one
• Opportunity to help build and lead the machine learning team

The Role

We're seeking a passionate machine learning leader (Senior/Manager level) who is motivated to meaningfully improve the way healthcare is administered in the United States. You'll take ownership of developing our AI/ML systems and models that power the Onos platform through hands-on development and technical leadership. As an early team member, you'll work closely with our founding team while helping to build and lead a growing machine learning team. This role is a hybrid role based in San Francisco, where you'll be expected to work at our office in person at least once a week.

What you'll be doing at Onos:

• Design, develop and deploy sophisticated ML models to analyze healthcare data, detect anomalies, and generate actionable insights
• Build LLM/NLU systems to process and extract meaningful information from clinical notes and medical documents
• Create ML pipelines that scale efficiently while maintaining strict data privacy and security standards
• Establish machine learning best practices, evaluation frameworks, and model governance for future team growth
• Collaborate with backend engineers to integrate ML capabilities seamlessly into the Onos platform

Technical Challenges At Onos:

• 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
• Design explainable AI solutions that provide transparency into model decisions for healthcare professionals
• Build ML pipelines to analyze handwritten clinical notes and automate recommendations for clinical reviewers
• Scale our systems to process millions of healthcare records while maintaining strict security and compliance requirements

What we're looking for:

• 5+ years experience building and deploying machine learning systems in production
• Proficiency with Python and related data science/ML libraries
• Experience with integrating ML systems with multiple user-facing features
• Familiarity with AWS cloud infrastructure for deploying ML solutions
• 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:

• Significant experience working with healthcare data and with HIPAA best practices
• Built and deployed large language models for production applications
• 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

Benefits and Perks

• Flexible hybrid arrangement: 1-2 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.