Senior Machine Learning Engineer, ML Training Platform
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet.
What this role actually needs.
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Responsibilities: - Lead the building, testing, and maintenance of ML training infrastructure at Reddit. - Play a pivotal role in designing, building, and optimizing the infrastructure and tooling required to support large-scale machine learning workflows. - Evolve the MLE experience, from provisioning interactive GPU environments through large-scale training, supporting on-demand and self-service workflows. - Kubernetes Automation: Write custom Kubernetes Controllers and Operators to manage the lifecycle of interactive Jupyter workspaces and long-running ML training jobs, handle auto-idling, and ensure fault tolerance. - GPU Orchestration: Work with the underlying compute team to ensure MLEs have efficient access to training hardware resources and handle resource contention gracefully. - Developer Experience (DevX): Treat internal MLEs as your customers. Conduct user research, reduce friction in the "Idea-to-Prototype" loop, and standardize software environments (Docker images, Python dependency management). Benefits: - Comprehensive Healthcare Benefits and Income Replacement Programs - 401k Match - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Flexible Vacation & Reddit Global Days off Company context: Reddit builds large-scale consumer, ads, and platform systems with hiring across mobile, backend, machine learning, and product engineering.
Day-to-day expectations
Reddit lists these responsibilities for the Senior Machine Learning Engineer, ML Training Platform role.
- Lead the building, testing, and maintenance of ML training infrastructure at Reddit.
- Play a pivotal role in designing, building, and optimizing the infrastructure and tooling required to support large-scale machine learning workflows.
- Evolve the MLE experience, from provisioning interactive GPU environments through large-scale training, supporting on-demand and self-service workflows.
- Kubernetes Automation: Write custom Kubernetes Controllers and Operators to manage the lifecycle of interactive Jupyter workspaces and long-running ML training jobs, handle auto-idling, and ensure fault tolerance.
- GPU Orchestration: Work with the underlying compute team to ensure MLEs have efficient access to training hardware resources and handle resource contention gracefully.
- Developer Experience (DevX): Treat internal MLEs as your customers. Conduct user research, reduce friction in the "Idea-to-Prototype" loop, and standardize software environments (Docker images, Python dependency management).
Why people would want this job
Reddit published these compensation, benefits, or working-context details with the role.
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k Match
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Reddit Global Days off
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Source: job-boards.greenhouse.io · Source ID: 7074776 · Confidence: 90/100 · Last checked: May 7, 2026
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