Software Engineer - MLOps

About Us

Phare Health, now part of R1 and its AI innovation engine, R37 Lab, is building the first AI-native Healthcare Revenue Operating System. This connected platform leverages frontier clinical reasoning technology to automate medical coding, billing, and follow-up by reasoning over full medical records, payer logic, and financial workflows. Our agentic AI systems are already powering production workflows across 95 of the top 100 U.S. health systems, processing hundreds of millions of patient encounters annually.

This role offers startup-level ownership with enterprise-level impact, focusing on building AI that ships, scales, and measurably improves healthcare operations.

The Role

As a Software Engineer - MLOps, you will own the production runtime for Phare’s ML stack. This includes deploying, serving, and scaling models across inference endpoints and batch/streaming workflows. You will be responsible for building progressive delivery pipelines with automated rollouts and rollbacks, managing SLOs for latency and availability, and instrumenting end-to-end observability (metrics, logs, traces, drift, regression). Furthermore, you will harden the platform using Terraform, Kubernetes, and CI/CD to ensure reproducible and auditable ML releases.

We are hiring across several seniority levels, from Mid-level up to Staff, and expect candidates to have at least 5 years of software engineering experience with a minimum of 2 years in ML Ops.

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

About You

You have a strong background in operating ML systems at scale, where uptime and feedback loops are as crucial as model accuracy. Your experience should include:

• Production ML: Deploying and operating models running on GPUs in production, including APIs and batch/streaming inference.
• Platform Engineering: Proficiency with Docker/Kubernetes, Infrastructure as Code (e.g., Terraform), and CI/CD for services and model artifacts. You should be adept at maintaining environment parity, reproducible releases, and robust model/experiment versioning with data lineage.
• System Reliability: Utilizing progressive delivery with automated rollouts/rollbacks, and building end-to-end observability (metrics, logs, traces, and model telemetry for drift/regression) along with actionable alerting, runbooks, and incident response.
• Post-training Lifecycles: Managing model registries and stage gates, designing scheduled or event-driven retraining, and enforcing RBAC, secrets management, encryption, and audit logs.
• Bonus: Experience in regulated environments (e.g., healthcare, finance).

Role Leveling

We are looking for candidates at various levels:

• L2: Independently delivers a complete end-to-end project, owning design, implementation, and delivery of scoped work.
• L3: Leads delivery of larger projects, handling increased technical complexity and ambiguity, providing light guidance to L2s on shared work.
• Senior: Team Lead responsible for managing a portfolio of projects that contribute to major technical initiatives.
• Staff: Impacts at the organizational level, leading multiple teams or broad initiatives simultaneously to ensure high-level technical goals are met across the entire organization.

Benefits

• Top-of-market compensation (salary + equity)
• Flexible PTO
• Hybrid in-office (minimum 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