Senior Systems ML Engineer: Scalable AI Infra

Meta; Cheyenne (WY); On-site; USD 154,000 - 217,000; Full time

Job summary

Meta is seeking a Software Engineer for the Systems ML Engineering team to build the ML infrastructure powering Meta's products at scale. You will design high‑performance ML systems across training and inference pipelines with hardware‑aware optimizations.

You will collaborate with researchers, platform engineers, and product teams to accelerate ML workloads, improve efficiency, and deploy AI‑informed workflows. This is a hands‑on, scale‑oriented role.

Qualifications

• BS/BE or higher in CS/Engineering or equivalent practical experience.
• 6+ years of software engineering with ML systems focus.
• Experience with ML training/inference pipelines (PyTorch/TF).
• Experience with distributed computing architectures for ML workloads.
• Proficiency in C++ and Python for performance‑critical systems.
• Experience using profiling tools to optimize ML/compute intensive workloads.

Responsibilities

• Design, build, and optimize large‑scale ML training and inference systems.
• Develop and maintain high‑performance ML infrastructure in C++ and Python.
• Identify bottlenecks using profiling, instrumentation, and benchmarking.
• Architect trade‑offs in ML system design (memory, compute, I/O).
• Collaborate with research and product teams to translate model requirements into infrastructure.
• Define system metrics and SLOs for production reliability of ML services.
• Lead design reviews and contribute to engineering standards for ML systems.
• Mentor engineers on ML infrastructure best practices and perf optimization.
• Drive AI‑augmented development workflows to improve productivity.

Skills

ML systems

Performance optimization

Distributed computing

Mentoring

System design

Education

Bachelor's degree in Computer Science/Engineering or equivalent

Tools

PyTorch

TensorFlow

CUDA

ROCm

MLIR

LLVM

TVM

XLA

IREE

Job description

Meta is seeking a Software Engineer for the Systems ML Engineering team to build the ML infrastructure powering Meta's products at scale. You will design high‑performance ML systems across training and inference pipelines with hardware‑aware optimizations.

You will collaborate with researchers, platform engineers, and product teams to accelerate ML workloads, improve efficiency, and deploy AI‑informed workflows. This is a hands‑on, scale‑oriented role.