Staff Machine Learning Engineer, ML Efficiency

📋 Description

• Design and build systems to improve ML training and inference efficiency.
• Develop tooling to debug, profile, optimize, and monitor model performance.
• Improve GPU and resource utilization via scheduling, caching, and workload optimization.
• Partner with ML researchers and product teams to identify bottlenecks and drive improvements.
• Build benchmarking frameworks and dashboards for training and serving.
• Optimize distributed training infra, data pipelines, and model serving architectures.
• Lead cross-functional initiatives to improve Reddit ML engineers' productivity.
• Drive technical strategy for ML platform scalability, reliability, and cost efficiency.

🎯 Requirements

• BS, MS, or PhD in Computer Science or related field.
• 5+ years of software engineering experience.
• Strong proficiency in Python.
• Proficiency in at least one systems language: Go, C++, Rust, or Java.
• Experience building distributed systems at scale.
• Experience with ML infrastructure, training systems, or model serving platforms.