ML Systems Engineer - Large-Scale, Low-Latency Infra

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

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.