Hims & Hers
Healthcare
StaffMachineLearningSystemsEngineer(MLOps)
Neural analysis suggests this role is
optimal for Senior candidates.
“Staff Machine Learning Systems Engineer (MLOps) at Hims & Hers. Skills: MLOps, Infrastructure Engineering, Cloud Platform. Own and scale AI compute platform. Evolve containerized application deployment platform”
What You'll Achieve.
Ensure AI systems reliable; Ensure AI systems observable; Ensure AI systems secure; Ensure AI systems trustworthy; Define how AI runs; Improve developer velocity
Industry & Context.
Root cause analysis; Troubleshooting; Debugging
What They're Looking For.
Must Have
5+ years infrastructure experience, Experience with Kubernetes, Experience with CI/CD pipelines, Experience with Infrastructure-as-Code, Experience with inference infrastructure, Experience with model-serving infrastructure, Experience with observability stack, Experience with tracing stack
Nice to Have
Experience with EKS clusters, Experience with deployment infrastructure, Experience with autoscaling infrastructure, Experience with IAM, Experience with secrets management, Experience with Langfuse, Experience with Datadog, Experience with OpenTelemetry, Experience with ClickHouse, Experience with Terraform, Experience with Scalr
What You'll Do.
Own and scale AI compute platform
Evolve containerized application deployment platform
Manage AI workloads orchestration
Operate Kubernetes clusters
Manage node lifecycle
Build GitOps deployment pipelines
Design ephemeral environments
Implement feature-branched deployments
Create nightly release pipelines
Operate inference infrastructure
Manage LLM gateway credentials
Manage LLM gateway rate limits
Manage LLM gateway failover
Build reliable serving patterns
Create infrastructure abstractions
Standardize AI service deployment
Standardize AI service configuration
Standardize AI service consumption
Own LLM/AI observability stack
Provision observability systems
Scale observability systems
Build analytics pipelines
Build monitoring pipelines
Surface latency signals
Surface error signals
Surface quality signals
Surface regression signals
Create on-call runbooks
Manage incident response
Troubleshoot AI lead issues
Raise platform reliability
Own and improve monorepo build system
Improve CI/CD pipelines
Manage eval workflows
Manage Docker image builds
Execute cross-platform tests
Own shared infrastructure tooling
Eliminate platform bottlenecks
Reduce CI/CD cycle times
Reduce deployment friction
Improve developer velocity
How You'll Work.
Team & Collaboration
Partner with ML engineers; Partner with product engineers; Partner with clinical teams; AI teams; Product engineers; Clinical teams; Applied AI organization
Process & Methodology
GitOps, CI/CD
Full Job Description
Hims & Hers is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. We are redefining healthcare by putting the customer first and delivering access to care that is affordable, accessible, and personal, from diagnosis to treatment to delivery. No two people are the same, so we provide access to personalized care designed for results. By normalizing health & wellness challenges and innovating on their solutions, we’re making better health outcomes easier to achieve. Hims & Hers is a public company, traded on the NYSE under the ticker symbol “HIMS.” To learn more about the brand and offerings, you can visit hims.com/about http://hims.com/about and hims.com/how-it-works http://hims.com/how-it-works . For information on the company’s outstanding benefits, culture, and its talent-first flexible/remote work approach, see below and visit www.hims.com/careers-professionals http://www.hims.com/careers-professionals. ABOUT THE ROLE: We're hiring a Staff ML Systems Engineer to design, build, and operate the production infrastructure that powers AI across Hims & Hers. This is a deeply technical, hands-on infrastructure role focused on the systems underneath AI — the Kubernetes platform, CI/CD and GitOps pipelines, infrastructure-as-code, inference and model-serving infrastructure, and the observability and tracing stack that keeps AI services reliable, debuggable, and compliant in production. You won't just deploy models — you'll own the machinery that lets every AI team ship and operate safely. You'll own critical systems like our EKS clusters, deployment and autoscaling infrastructure, IAM and secrets management, LLM tracing/observability pipelines (Langfuse, Datadog, OpenTelemetry), and the developer platform that AI and product engineers rely on daily. You'll partner with ML engineers, product engineers, and clinical teams to ensure our AI systems are reliable, observable, secure, and trustworthy in a regul
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