Senior Machine Learning Engineer, ML Training Platform
Job description
Who We Are:
The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams.
What You’ll Do:
As a Senior Software Engineer, Machine Learning Platform (Training Platform), you will be instrumental in architecting, implementing, and maintaining foundational Machine Learning (ML) infrastructure that powers Feeds Ranking, Content Understanding, Recommendations and much more to fulfill Reddit’s mission of bringing community and belonging to everyone in the world. You will deliver a self service ML platform that enables the continuous iteration and improvement of systems that use ML techniques including Deep Learning, Natural Language Processing, Recommendation Systems, Representation Learning and Computer Vision.
- 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).
Who You Might Be:
- 5+ years of software engineering experience, with a focus on Platform Engineering, ML Infrastructure, or Backend Systems.
- Deep Kubernetes Expertise: You know K8s beyond just "deploying pods." You understand CRDs, Controllers and the Operator pattern.
- Jupyter Ecosystem Knowledge: Experience customizing JupyterHub, JupyterLab extensions, or building similar interactive computing platforms.
- Strong Coding Skills: Proficiency in Python (for the ML ecosystem) and Go (for Kubernetes controllers/infrastructure tooling).
- GPU Experience: Hands-on practice with CUDA environments, GPU virtualization/containerization, and doing it all within Kubernetes.
- Cloud Provider Experience: Familiarity with both managed ML offerings (Vertex AI, Sagemaker, etc) and building custom ML components in AWS and/or GCP.
- Experience working with distributed training frameworks, including Ray and Kubernetes.
- Comfortable with distributed systems, big data (Petabyte scale) and data-intensive systems.
- Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the machine learning development lifecycle.
- Strong organizational & communication skills.
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
- Generous paid Parental Leave
- Paid Volunteer time off
#LI-Remote
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
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Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.