Senior Systems ML Engineer - Scalable AI Infra

Meta; Raleigh (NC); On-site; USD 154,000 - 217,000; Full time

Job summary

Meta is seeking a Software Engineer for the Systems ML Engineering team to design and optimize machine learning infrastructure at massive scale. You will work across model training, inference pipelines, and hardware-aware optimizations, collaborating with researchers and product teams to accelerate ML workloads.

Responsibilities include building high-performance ML infrastructure in C++/Python, profiling for bottlenecks, and guiding ML system design trade-offs.

Qualifications

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

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

Profiling tools

Distributed computing

Education

Bachelor's degree in CS/Engineering

Tools

PyTorch

TensorFlow

CUDA

Job description

Meta is seeking a Software Engineer for the Systems ML Engineering team to design and optimize machine learning infrastructure at massive scale. You will work across model training, inference pipelines, and hardware-aware optimizations, collaborating with researchers and product teams to accelerate ML workloads.

Responsibilities include building high-performance ML infrastructure in C++/Python, profiling for bottlenecks, and guiding ML system design trade-offs.