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R1 RCM

Software Engineer – ML Ops

R1 RCM

. Own the production runtime for Phare’s ML stack .

Posted 10/8/2026full-timeNew York City • New York • United StatesMid-LevelSenior💰 $140,000 - $270,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in deploying and managing machine learning systems at scale, with a strong focus on CI/CD practices, infrastructure as code, and end-to-end observability. Proficient in using tools like Terraform and Kubernetes to ensure robust and reproducible ML releases.

Highest-signal resume keywords
Machine Learning Systems ManagementCI/CD ExperienceTerraform ProficiencyKubernetes ExpertiseEnd-to-End Observability

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Machine Learning DeploymentModel ServingBatch InferenceStreaming InferenceInfrastructure as CodeModel VersioningData LineageAutomated RolloutsIncident ResponseRBAC Knowledge
Tools & Technologies
DockerKubernetesTerraformCI/CD ToolsModel Registries
Industry Keywords
Regulated EnvironmentsHealthcareFinance

Tech Stack

Tools & technologies
DockerKubernetesTerraform

About the role

Key responsibilities & impact
  • Own the production runtime for Phare’s ML stack
  • Deploy, serve, and scale models across inference endpoints and batch/streaming workflows
  • Build progressive delivery pipelines with automated rollouts and rollbacks
  • Manage SLOs for latency and availability
  • Instrument end-to-end observability, including metrics, logs, traces, drift, and regression
  • Harden the platform with Terraform, Kubernetes, and CI/CD
  • Ensure reproducible and auditable ML releases
  • Deliver end-to-end projects, lead larger projects, or manage portfolios and broad technical initiatives depending on level

Requirements

What you’ll need
  • Background in operating ML systems at scale
  • Experience deploying and operating models running on GPUs in production, including APIs and batch/streaming inference
  • Strong Docker/Kubernetes skills
  • Infrastructure as code experience, such as Terraform
  • CI/CD experience for services and model artifacts
  • Ability to maintain environment parity, reproducible releases, robust model/experiment versioning, and data lineage
  • Experience with progressive delivery, automated rollouts/rollbacks, end-to-end observability, actionable alerting, runbooks, and incident response
  • Experience managing model registries and stage gates
  • Ability to design scheduled or event-driven retraining
  • Knowledge of RBAC, secrets management, encryption, and audit logs
  • Experience in regulated environments such as healthcare or finance is a bonus
  • Candidates at levels ranging from Level 2 to Staff

Benefits

Comp & perks
  • Top-of-market compensation, including bonus that starts at 10%
  • Flexible PTO
  • Comprehensive health benefits
  • 401(k) matching
  • Inspiring, brilliant, mission-driven teammates
  • Opportunity to constantly learn, collaborate across groups and explore new paths for your career
  • Competitive benefits package