Staff Machine Learning Engineer, ML Efficiency

Requirements

• BS, MS, or PhD in Computer Science or a related field
• 5+ years of software engineering experience
• Strong proficiency in Python
• Experience building distributed systems at scale
• Experience with machine learning infrastructure, training systems, or model serving platforms
• Deep understanding of performance engineering and systems optimization
• Strong debugging and profiling skills

Nice to Haves

• Experience with large-scale recommendation, ranking, generative AI, or foundation model systems
• Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, Spark
• Familiarity with GPU architectures and performance analysis tools
• Experience optimizing cloud infrastructure costs across large ML workloads
• Contributions to internal platforms used by multiple ML teams
• Experience with building real-time ML inference applications

What You'll Be Doing

• Design and build systems that improve the efficiency of ML training and inference workloads
• Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance
• Improve GPU and general resource utilization through scheduling, resource management, caching, and workload optimization
• Optimize distributed training infrastructure, data pipelines, and model serving architectures
• Lead cross-functional initiatives that improve the productivity of Reddit ML engineers
• Drive technical strategy for ML platform scalability, reliability, and cost efficiency

Perks and Benefits

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Group Personal Pension Scheme with Employer match
• Private Medical and Dental Scheme
• Income Replacement Programs
• Bike to Work scheme
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave