Principal Systems ML Engineer, Infrastructure & AI Tools

Meta; Phoenix (AZ); On-site; USD 219,000 - 301,000; Full time

Job summary

Meta is seeking a principal-level Software Engineer to drive architectural foundations for large-scale ML infrastructure, spanning training systems, inference pipelines, ML compilers, high-performance computing frameworks, and on-device optimization. You will define multi-year roadmaps and raise the bar across cross-functional teams.

You will mentor engineers, translate complex ML systems concepts into clear design docs, and partner with research, hardware, and product teams to deliver

Qualifications

• Bachelors degree in Computer Science, Computer Engineering, or related field
• 12+ years of software engineering with deep specialization in ML systems including AI infrastructure, ML compilers, HPC, GPU architecture, ML frameworks, or on-device optimization
• Experience architecting and delivering large-scale ML training/inference infrastructure across multiple orgs
• Experience leading multi-year cross-functional technical initiatives with metrics, dependencies, and execution
• Experience developing high-performance ML systems infrastructure in C++, Python, or CUDA, including HW-SW intersections
• Experience influencing technical direction through proposals, reviews, and stakeholder alignment

Responsibilities

• Identify and solve the most complex cross-system ML infrastructure challenges across training, inference, compilers, and hardware-software co-design
• Define extensible architectural standards for ML systems enabling consistency and reliability
• Develop and own the multi-year technical roadmap for ML systems infrastructure
• Leverage AI-native tooling to reduce engineering toil and accelerate cross-disciplinary work
• Drive performance improvements across large-scale ML training and inference systems
• Establish invariants, correctness proofs, and systemic reliability practices
• Partner with research, hardware, and product teams to translate ML advances into production infrastructure
• Assess emerging AI technologies and influence organizational strategy
• Mentor engineers and foster high craftsmanship in ML systems development
• Communicate ML systems architecture and strategy clearly via design documents and roadmaps

Skills

Cross-system ML

Architectural foundations

Roadmap development

AI-native tooling

Performance optimization

Reliability practices

Mentoring engineers

Stakeholder communication

Education

Bachelor7s degree in Computer Science/Engineering or related field

Tools

C++

Python

CUDA

Job description

Meta is seeking a principal-level Software Engineer to drive architectural foundations for large-scale ML infrastructure, spanning training systems, inference pipelines, ML compilers, high-performance computing frameworks, and on-device optimization. You will define multi-year roadmaps and raise the bar across cross-functional teams.

You will mentor engineers, translate complex ML systems concepts into clear design docs, and partner with research, hardware, and product teams to deliver