Senior Systems ML Engineer - Scalable AI Infra

Meta; Montpelier (VT); On-site; USD 154,000 - 217,000; Full time

Job summary

Meta is seeking a Software Engineer to join the Systems ML Engineering team, building and optimizing the machine learning infrastructure that powers Meta's products at massive scale.

In this role you will design and develop high-performance ML systems, spanning from model training and inference pipelines to hardware-aware optimizations, collaborating across researchers, platform engineers, and product teams.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• 6+ years of software engineering experience with ML systems or high-performance computing.
• Experience with ML training/inference pipelines (PyTorch, TensorFlow).
• Experience with distributed computing architectures and large-scale ML workloads.
• Experience in C++ and Python for performance-critical systems.
• Experience with profiling/performance analysis tools.

Responsibilities

• Design, build, and optimize large-scale ML training and inference systems, including distributed computing frameworks and hardware-accelerated pipelines
• Develop and maintain high-performance ML infrastructure components in C++ and Python, ensuring reliability, scalability, and low-latency execution
• Identify and resolve performance bottlenecks across the ML stack using profiling, instrumentation, and benchmarking tools
• Architect and evaluate trade-offs in ML system design, including memory bandwidth, compute utilization, and I/O throughput
• Partner with research and product teams to translate ML model requirements into efficient infrastructure solutions
• Define and track system‑level metrics and service level objectives to maintain production reliability of ML serving systems
• Lead technical design reviews and contribute to engineering standards for ML systems across the organization
• Mentor other engineers on ML infrastructure best practices, debugging methodologies, and performance optimization techniques
• Drive adoption of AI‑augmented development workflows to expand engineering productivity and broaden the scope of deliverables
• Contribute to staged rollout strategies using feature flagging and experimentation frameworks to safely deploy ML system changes

Skills

C++

Python

ML infrastructure

Distributed systems

Performance optimization

Profiling tools

Team mentorship

Education

Bachelor's degree in CS/Engineering

Tools

PyTorch

TensorFlow

Job description

Meta is seeking a Software Engineer to join the Systems ML Engineering team, building and optimizing the machine learning infrastructure that powers Meta's products at massive scale.

In this role you will design and develop high-performance ML systems, spanning from model training and inference pipelines to hardware-aware optimizations, collaborating across researchers, platform engineers, and product teams.