Systems ML Engineer: Scalable AI Infrastructure

Meta; Richmond (VA); On-site; USD 154,000 - 217,000; Full time

Job summary

Meta is recruiting a Software Engineer for the Systems ML Engineering team to build and optimize the machine learning infrastructure powering Meta’s products at scale. You will design high-performance ML systems, from model training and inference pipelines to hardware-aware optimizations, collaborating with researchers, platform engineers, and product teams.

You will mentor engineers, drive ML infrastructure improvements, and help expand AI-driven development workflows with robust, measurable

Qualifications

• Bachelor's degree or equivalent practical experience.
• 6+ years in software engineering focusing on ML systems.
• Experience building ML training or inference pipelines with PyTorch/TensorFlow.
• Experience with distributed architectures for ML workloads.
• Proficient in C++ and Python for performance-critical systems.
• Experience with profiling/benchmarking tools.

Responsibilities

• Design and optimize large-scale ML training and inference systems.
• Develop high-performance ML infrastructure components.
• Identify and resolve performance bottlenecks across the ML stack.
• Lead design reviews and set engineering standards.
• Mentor engineers and promote AI-driven development workflows.

Skills

ML training systems

C++ & Python

Performance profiling

Distributed computing

ML infrastructure

System design

Mentoring

Education

Bachelor's degree in CS/Engineering

Tools

PyTorch

TensorFlow

Job description

Meta is recruiting a Software Engineer for the Systems ML Engineering team to build and optimize the machine learning infrastructure powering Meta’s products at scale. You will design high-performance ML systems, from model training and inference pipelines to hardware-aware optimizations, collaborating with researchers, platform engineers, and product teams.

You will mentor engineers, drive ML infrastructure improvements, and help expand AI-driven development workflows with robust, measurable