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.
Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements.
Build benchmarking frameworks and performance dashboards for training and serving systems.
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.

BS, MS, or PhD in Computer Science or a related field.
5+ years of software engineering experience.
Strong proficiency in Python
Profiency in at least one systems language (Go, C++, Rust, or Java) preferred
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.

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

Staff Machine Learning Engineer, ML Efficiency

Key skills