Staff Machine Learning Engineer, GenAI Platform

• →10+ years of work experience in a production software development environment or building complex distributed data systems, plus a degree in ML, Engineering, Computer Science, or a related discipline.
• →GenAI/LLM Infrastructure Expertise: Proven track record of designing and operating large-scale ML systems, specifically working with distributed training frameworks (e.g., FSDP, DeepSpeed, Megatron-LM) and LLM serving/inference optimization (e.g., vLLM, TensorRT-LLM).
• →Distributed Systems Mastery: Hands-on experience managing fault-tolerant, petabyte-scale distributed systems and multi-node/multi-GPU training clusters.
• →Advanced MLOps Knowledge: Deep understanding of modern ML orchestration, fine-tuning pipelines, and model evaluation methodologies. Experience with tools like Ray, MLflow, or similar ecosystem standards.
• →GPU Experience: Hands-on practice with CUDA environments, GPU virtualization/containerization, and doing it all within Kubernetes.
• →Production Engineering Fundamentals: Hands-on experience with Kubernetes, Docker, and building production-quality, object-oriented code in Python and/or Go.
• →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.

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.