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Phare Health

ML Engineer

Reposted 19 Days Ago
In-Office
New York, NY
175K-300K Annually
Senior level
In-Office
New York, NY
175K-300K Annually
Senior level
The Machine Learning Engineer will develop the internal ML environment, partnering with research to ensure models are production-ready and optimizing infrastructure performance.
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About Phare & R1

Phare is building healthcare’s first Revenue Operating System - a platform that uses AI to make hospital billing and reimbursement effortless, accurate, and fair. We recently became part of R1, one of the largest companies managing healthcare claims which serves hundreds of systems around the country. This gives us the best of both worlds: the DNA of an AI startup paired with the scale of a healthcare organization that supports care delivery for hundreds of healthcare systems nationwide. Join us on our mission to build a fairer, faster model for healthcare payments.

The Role

As a Machine Learning Engineer, you will own the internal ML dev environment (instrumentation, benchmarking, experimentation) so ideas move rapidly from research to validated pipelines. You’ll partner closely with the research to make models production-ready - with clear handoff contracts, performance gates, and packaging standards-and with ML Platform & Ops for safe rollouts.

We are hiring across several seniority levels ranging from Mid-level up to Staff. At a minimum, we would expect 5 years of software engineering experience with 2 years of ML Eng experience.

This is an in-person role in NYC requiring at least 3 days in the SoHo office.

About you

You’re an ML engineer who thrives at the intersection of research and production - someone who sees the research team as your primary customer and loves building the internal engines that let ideas ship faster.

You have experience:

  • Building training and inference infrastructure for a fast-moving research team including experiment tracking and benchmarking.

  • Operating modern orchestration/compute and accelerators at scale (e.g., Ray, Airflow, Kubernetes) and optimizing performance and cost tradeoffs.

  • Building agentic workflows, familiarity with agent orchestration.

  • Liaising between Research & MLOps to establish handoff contracts, performance gates, and rollout standards.

  • Staying up to date with ML literature and engineering best practices

Benefits

  • Top-of-market compensation (salary + equity)

  • Flexible PTO

  • Hybrid in-office (min. 3 days per week)

  • Comprehensive health benefits

  • 401(k) matching

  • Inspiring, brilliant, mission-driven teammates

Hiring Flow

  • Intro call - your background & our mission alignment

  • Technical deep-dives - pseudo-coding exercise and systems design (not Leetcode)

  • Culture interview in person in NYC

  • References

  • Offer

Top Skills

AI
Airflow
Kubernetes
Ml
Ray
HQ

Phare Health New York, New York, USA Office

New York, New York, United States

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