Software Engineer, Systems ML

Meta Careers; Menlo Park, Northern (CA, KY); Hybrid; USD 180,000 - 300,000; Full time

Job summary

Meta is hiring a Software Engineer for the Systems ML team in Menlo Park, CA. You will design and optimize large-scale ML training and inference systems, spanning the full stack from pipelines to hardware-aware optimizations.

You will collaborate with researchers, platform engineers, and product teams to accelerate workloads and improve AI infrastructure for billions of users, ensuring reliability and low-latency performance.

Qualifications

• Experience designing and building large-scale ML training and inference systems.
• Strong knowledge of distributed systems, low-latency pipelines, and memory management.
• Proficiency in C++ and Python for production ML infrastructure.

Responsibilities

• Design, build, and optimize large-scale ML training and inference systems.
• Develop and maintain high-performance ML infrastructure components in C++ and Python.
• Identify and resolve performance bottlenecks across the ML stack using profiling and benchmarking.
• Architect trade-offs in ML system design, including memory bandwidth and throughput.
• Partner with research and product teams to translate model requirements into scalable infrastructure.
• Write automated tests and monitoring for production ML components.
• Contribute to staged rollout strategies with feature flags and experiments.

Skills

C++

Python

Distributed systems

Profiling

ML infrastructure

Education

BS in CS

Tools

CUDA

Profiling tools

Job description

# Software Engineer, Systems MLMenlo Park, CA Engineering+ 2 moreApply nowMeta is seeking a Software Engineer to join our Systems ML Engineering team, focused on building and optimizing the machine learning infrastructure that powers Meta's products at massive scale. In this role, you will design and develop high-performance ML systems, working across the full stack from model training and inference pipelines to hardware-aware optimizations. You will collaborate with researchers, platform engineers, and product teams to accelerate ML workloads and improve the efficiency of AI infrastructure that serves billions of users.---## Software Engineer, Systems ML Responsibilities* Design, build, and optimize large-scale ML training and inference systems, including distributed computing frameworks and hardware-accelerated pipelines* Develop and maintain high-performance ML infrastructure components in C++ and Python, ensuring reliability, scalability, and low-latency execution* Identify and resolve performance bottlenecks across the ML stack using profiling, instrumentation, and benchmarking tools* Architect and evaluate trade-offs in ML system design, including memory bandwidth, compute utilization, and I/O throughput* Partner with research and product teams to translate ML model requirements into efficient infrastructure solutions* Write automated tests covering expected behaviors, failure modes, and error paths for ML infrastructure components, and build monitoring and alerting for production anomalies* Contribute to staged rollout strategies using feature flagging and experimentation frameworks to safely deploy ML system changes