Systems ML Engineer - Compilers & Accelerators (Equity)

Meta; Bellevue (WA); On-site; USD 154,000 - 217,000; Full time

Job summary

Meta is seeking a Software Engineer to design, build, and optimize systems-level ML infrastructure that powers large AI workloads across production environments. The role focuses on compiling, kernels, and high-performance runtimes that enable efficient training and inference on Meta's distributed compute fabric.

You will collaborate with researchers and hardware teams to map models to accelerated platforms, drive performance and reliability, and contribute to tooling, testing, and incident

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience.
• 6+ years of software engineering with a focus on systems software, ML infrastructure, or distributed computing.
• Experience designing and optimizing software systems for large-scale ML training or inference workloads.
• Experience with performance analysis and optimization techniques including profiling and low-level systems tuning.
• Experience building reliable, production-grade distributed systems with observability, monitoring, and incident response practices.
• Experience communicating technical decisions through design documents and proposals.

Responsibilities

• Design and implement scalable systems-level software components that support large-scale ML training and inference workloads across distributed compute infrastructure.
• Identify and resolve performance bottlenecks in ML pipelines through profiling and targeted optimization of compute, memory, and I/O utilization.
• Develop and maintain high-quality, well-tested software for ML runtime systems, including scheduling, resource management, and execution frameworks.
• Collaborate with AI researchers and hardware teams to map deep learning models onto accelerated hardware platforms.
• Own the technical design of systems components, evaluating trade-offs across correctness, performance, reliability, and maintainability.
• Establish and monitor service-level objectives and performance metrics for ML infrastructure systems, building dashboards and alerting to reduce MTTR.
• Drive adoption of engineering best practices including automated testing, staged rollout strategies with feature flags and AB testing frameworks, and documentation.
• Mentor other engineers through growth areas, code and design reviews, and cross-functional collaboration.

Skills

Systems software

ML infrastructure

Distributed computing

Performance profiling

Observability

Design documentation

Education

Bachelor's degree in Computer Science or related field

Tools

PyTorch

TensorFlow

JAX

MLIR/LLVM

Job description

Meta is seeking a Software Engineer to design, build, and optimize systems-level ML infrastructure that powers large AI workloads across production environments. The role focuses on compiling, kernels, and high-performance runtimes that enable efficient training and inference on Meta's distributed compute fabric.

You will collaborate with researchers and hardware teams to map models to accelerated platforms, drive performance and reliability, and contribute to tooling, testing, and incident