Senior Systems ML Engineer – Large-Scale AI Infra

Meta; New York (NY); On-site; USD 154,000 - 217,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Meta is seeking a Software Engineer for the Systems ML Engineering team to design and optimize large-scale ML training and inference systems, spanning from model pipelines to hardware-aware optimizations.

You will collaborate with researchers, platform engineers, and product teams to accelerate ML workloads and improve AI infrastructure serving billions of users. This role emphasizes high-performance C++ and Python development, profiling, and scalable systems design.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or equivalent.
• 6+ years in software engineering focused on ML systems or AI infrastructure.
• Experience with ML training/inference pipelines using PyTorch, TensorFlow, or equivalent.
• Experience with distributed architectures and large-scale ML workloads.
• Proficient in C++ and Python for performance-critical systems.
• Experience using profiling tools to identify bottlenecks.

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

ML systems

Distributed computing

Python programming

Performance profiling

Education

Bachelor's degree in CS/Engineering or equivalent

Tools

C++

Python

PyTorch

TensorFlow

Job description

Meta is seeking a Software Engineer for the Systems ML Engineering team to design and optimize large-scale ML training and inference systems, spanning from model pipelines to hardware-aware optimizations.

You will collaborate with researchers, platform engineers, and product teams to accelerate ML workloads and improve AI infrastructure serving billions of users. This role emphasizes high-performance C++ and Python development, profiling, and scalable systems design.