Principal Systems ML Engineer - Scale AI Infrastructure

Meta; United States; Hybrid; USD 300,000 - 420,000; Full time

Job summary

Meta is seeking a principal-level Software Engineer to drive strategy and execution across our Systems ML Engineering organization. You will define the architectural foundations that power large-scale machine learning infrastructure, spanning training systems, inference pipelines, ML compilers, high-performance computing frameworks, and on-device optimization.

You will identify and solve the hardest cross-system ML infrastructure challenges, shaping multi-year roadmaps and amplifying engineering

Qualifications

• Bachelor's degree or equivalent practical experience.
• 12+ years in software engineering with ML systems specialization.
• Experience delivering large-scale ML training/inference infra with cross-team impact.
• Experience leading multi-year cross-functional technical initiatives.
• Strong C++, Python, or CUDA development.
• Ability to influence direction across teams through proposals and reviews.
• Commitment to responsible, ethical AI practices.

Responsibilities

• Define architectural foundations for ML infrastructure.
• Drive multi-year roadmaps for training, inference, and AI tooling.
• Lead cross-functional initiatives across teams and stakeholders.
• Advance high-performance ML systems, AI efficiency, and reliability.

Skills

ML systems

C++

Python

CUDA

GPU architecture

AI infrastructure

ML frameworks

Cross-functional leadership

Education

Bachelor's degree in Computer Science or related field

Tools

MLIR

XLA

TVM

Job description

Meta is seeking a principal-level Software Engineer to drive strategy and execution across our Systems ML Engineering organization. You will define the architectural foundations that power large-scale machine learning infrastructure, spanning training systems, inference pipelines, ML compilers, high-performance computing frameworks, and on-device optimization.

You will identify and solve the hardest cross-system ML infrastructure challenges, shaping multi-year roadmaps and amplifying engineering