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# Software Engineer

- **Company:** R1 RCM Inc.
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $140,000.0 - $300,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Audit Trail, Continuous Integration, Key Management, Role-Based Access Control, Software Engineering, Management of Software Versions, Graphics Processing Unit (GPU), Reliability of Systems, Kubernetes, Data Lineage, Machine Learning Operations, Terraform, Docker
- **Published:** September 24, 2026
- **Apply:** https://www.thejobnetwork.com/job/software-engineer-mlops-509978594

## About the Role

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

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

About you

You have a background in operating ML systems at scale, where uptime and feedback loops matter as much as accuracy.

Additionally, you have experience in:

 * Production ML: You've deployed and operated models running on GPUs in production - APIs and batch/streaming inference
 * Platform engineering: Strong with Docker/Kubernetes, IaaC (e.g., Terraform), and CI/CD for services and model artifacts; you maintain environment parity, reproducible releases, and robust model/experiment versioning with data lineage
 * System Reliability: You use progressive delivery with automated rollouts/rollbacks, and you build end-to-end observability (metrics, logs, traces, and model telemetry for drift/regression) plus actionable alerting, runbooks, and incident response
 * Post-training lifecycles: You manage model registries and stage gates, design scheduled or event-driven retraining when appropriate, and enforce RBAC, secrets management, encryption, and audit logs
 * Bonus: Experience in regulated environments (e.g., healthcare, finance)

## Description

You'll own the production runtime for Phare's ML stack - deploying, serving, and scaling models across inference endpoints and batch/streaming workflows. You'll build progressive delivery pipelines with automated rollouts and rollbacks, manage SLOs for latency and availability, and instrument end-to-end observability (metrics, logs, traces, drift, regression). You'll harden the platform with Terraform, Kubernetes, and CI/CD, ensuring reproducible, auditable ML releases., We are looking for candidates at various levels, ranging from Level 2 to Staff

 * 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: Impact at the organizational level. Responsible for leading multiple teams or multiple broad initiatives simultaneously, ensuring that high-level technical goals are met across the entire organization.