Senior Systems ML Engineer: Scalable AI Infrastructure

Meta; Providence (RI); 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 and optimize ML infrastructure at massive scale. You will design high-performance ML systems, from training to inference pipelines, and work across the full stack for hardware-aware optimizations.

You will collaborate with researchers, platform engineers, and product teams to accelerate ML workloads, define metrics, and lead reviews while mentoring others in ML infrastructure best practices.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
• 6+ years of software engineering focusing on ML systems, AI infrastructure, or HPC.
• Experience developing and optimizing ML training or inference pipelines (PyTorch, TensorFlow or equivalent).
• Experience with distributed computing architectures and large-scale ML systems design.
• C++ and Python for performance-critical systems.
• Experience using profiling and performance analysis tools to identify bottlenecks.

Responsibilities

• Design, build, and optimize large-scale ML training and inference systems, including distributed frameworks and hardware-accelerated pipelines.
• Develop and maintain high-performance ML infrastructure components in C++ and Python.
• Identify and resolve performance bottlenecks across the ML stack using profiling and benchmarking tools.
• Architect and evaluate trade-offs in ML system design including memory bandwidth and I/O throughput.
• Partner with research and product teams to translate ML model requirements into infrastructure solutions.
• Define and track system-level metrics and SLAs to maintain production reliability of ML serving systems.
• Lead technical design reviews and contribute to ML engineering standards.
• Mentor engineers on ML infrastructure best practices and performance optimization.
• Drive adoption of AI-augmented development workflows to expand engineering productivity.
• Contribute to staged rollout strategies using feature flags and experimentation frameworks.

Skills

ML systems design

C++/Python infra

Performance profiling

System design trade-offs

Cross-functional collaboration

SLA metrics

Technical leadership

Mentorship

AI-powered workflows

Feature flags/ rollout

ML pipelines

Distributed systems

Profiling tools

Education

Bachelor's degree or equivalent

Tools

CUDA/ROCm

Job description

Meta is seeking a Software Engineer for the Systems ML Engineering team to build and optimize ML infrastructure at massive scale. You will design high-performance ML systems, from training to inference pipelines, and work across the full stack for hardware-aware optimizations.

You will collaborate with researchers, platform engineers, and product teams to accelerate ML workloads, define metrics, and lead reviews while mentoring others in ML infrastructure best practices.