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Software Engineer, Systems ML

Meta· Systems ML Engineering
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Sunnyvale, CA$154k - $217kFull-timePosted 3mo ago

About the role

Meta is seeking a Software Engineer to join the Systems ML Engineering team, focused on building and optimizing machine learning infrastructure that powers Meta's products at massive scale. Design and develop high-performance ML systems across the full stack from model training and inference pipelines to hardware-aware optimizations, collaborating with researchers, platform engineers, and product teams to accelerate ML workloads and improve AI infrastructure efficiency.

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

Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 6+ years of experience in software engineering with a focus on machine learning systems, AI infrastructure, or high-performance computing
  • Experience developing and optimizing ML training or inference pipelines using frameworks such as 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

Skills

Required:ML system design and optimizationC++PythonProfiling and performance analysis

Benefits

  • Bonus
  • Equity
  • Benefits
Last updated Oct 23, 2026. Interested? Apply on the company site.

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