Staff ML Systems Engineer

Meta; Bellevue (WA); On-site; USD 183,997 - 257,000; Full time

Job summary

Meta is seeking a Staff Software Engineer to join the Systems ML Engineering team, focusing on building and scaling the infrastructure and software systems that power large-scale machine learning workloads across Meta's production fleet.

You will architect and own critical components of the ML systems stack, spanning training infrastructure, model serving, distributed computing frameworks, and ML platform tooling.

Qualifications

• Bachelor's degree in CS, CE or equivalent practical experience.
• 8+ years in software engineering focusing on systems, distributed computing, or ML infrastructure.
• Experience designing large-scale distributed systems (training orchestration, model serving, data pipelines).
• Experience with C++ or Python in production ML or infrastructure systems.
• Strong profiling and optimization skills.

Responsibilities

• Design and implement scalable ML systems infrastructure components across production workloads.
• Lead technical design for major ML infrastructure initiatives with focus on performance and reliability.
• Identify and resolve performance bottlenecks in distributed ML training and inference.
• Define SLAs for ML infrastructure services with dashboards, alerts, and runbooks.
• Collaborate with researchers, product engineers, and infra teams to translate requirements into production systems.
• Leverage AI-assisted development workflows while applying domain expertise judiciously.
• Mentor engineers on ML systems practices and distributed computing patterns.
• Drive adoption of testing, staged rollout, and monitoring practices.
• Contribute to ML infra roadmap and stakeholder alignment across teams.
• Conduct code reviews and establish coding standards for maintainable codebase.

Skills

C++

Python

Distributed systems

Performance optimization

Mentorship

Education

Bachelor's degree or equivalent

Tools

CUDA

PyTorch

Job description

Meta is seeking a Staff Software Engineer to join the Systems ML Engineering team, focusing on building and scaling the infrastructure and software systems that power large-scale machine learning workloads across Meta's production fleet.

You will architect and own critical components of the ML systems stack, spanning training infrastructure, model serving, distributed computing frameworks, and ML platform tooling.