Senior Machine Learning Engineer - ML Training Platform

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.

The base salary range for this position is:

$216700—$303400 USD