Software Engineer, Systems Machine Learning

Meta Careers; Menlo Park (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Meta seeks a Software Engineer to join the MTIA Software Tooling team, building tooling for Meta's in-house AI accelerators. You will design, build, and maintain developer tools to help engineers debug, profile, measure, and monitor AI workloads running on MTIA hardware at scale.

This role sits at the intersection of compilers, runtime, hardware, and ML frameworks, with collaboration across teams to deliver a high-quality developer experience for Meta's custom accelerators.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience.
• 2+ years of experience in software engineering with exposure to systems software, developer tooling, or infrastructure.
• Proficiency in C++ and Python, including systems-level programming concepts.
• Experience across multiple layers of a system stack (application, runtime, OS/driver, or hardware interfaces).
• Track record of independently delivering software projects from design through production deployment.
• Experience debugging and resolving issues in complex software systems (e.g., log analysis, stack traces).
• Experience building developer tools such as debuggers, profilers, build systems, CLI tools, monitoring dashboards, or diagnostic utilities.
• Exposure to accelerator ecosystems (GPU/CUDA, TPU, custom ASICs) or heterogeneous computing environments.
• Familiarity with Linux debugging and profiling tools (gdb, perf, strace, eBPF, valgrind).
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact.
• Experience adhering to and implementing responsible, ethical AI practices.
• Demonstrated ongoing AI skill development and staying current with emerging AI technologies.
• Contributions to open-source projects demonstrating tooling or system software interest.
• Experience in using data-driven methods to evaluate tooling effectiveness and to prioritize improvements.

Responsibilities

• Design, build, and maintain developer tools for MTIA hardware workloads.
• Debug, profile, measure, and monitor AI workloads at scale.
• Collaborate with cross-functional teams to deliver a high-quality developer experience for Meta's custom accelerators.

Skills

C++

Python

Systems software

Developer tooling

Cross-layer systems

Linux debugging tools

Distributed systems

AI tooling integration

Open-source contributions

MLIR/LLVM/TVM

Education

Bachelor's degree in Computer Science

Bachelor's degree in Computer Engineering

Equivalent practical experience

Tools

LLVM

MLIR

TVM

GDB

Perf

Strace

eBPF

Valgrind

Job description

Meta is seeking a Software Engineer to join the MTIA (Meta Training & Inference Accelerator) Software Tooling team, which develops and maintains the tooling ecosystem for Meta's in-house AI accelerator ASICs. The Tooling team provides debugging, profiling, memory analysis, and monitoring capabilities for the whole MTIA Ecosystem, redefining ML accelerator tooling by leveraging Meta's full-stack ownership from silicon specs to fleet observability. In this role, you will design, build, and maintain developer tools that help engineers debug, profile, measure, and monitor AI workloads running on MTIA hardware at scale. You will work at the intersection of compilers, runtime, hardware, and ML frameworks, collaborating with cross-functional partners to deliver a high-quality developer experience for Meta's custom AI accelerators.

Qualifications and Experience Requirements

• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Degree must be completed prior to joining Meta Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience 2+ years of experience in software engineering, with exposure to systems software, developer tooling, or infrastructure
• Proficiency in C++ and Python, including systems-level programming concepts
• Experience working across multiple layers of a system stack (e.g., application, runtime, OS/driver, or hardware interfaces)
• Track record of independently delivering software projects from design through production deployment
• Experience debugging and resolving issues in complex software systems (e.g., using log analysis, stack traces, or system-level diagnostic tools)
• Experience building developer tools such as debuggers, profilers, build systems, CLI tools, monitoring dashboards, or diagnostic utilities
• Exposure to accelerator ecosystems (GPU/CUDA, TPU, custom ASICs) or heterogeneous computing environments
• Familiarity with Linux debugging and profiling tools (gdb, perf, strace, eBPF, valgrind) or similar diagnostic infrastructure
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Contributions to open-source projects demonstrating tooling or system software interest
• Experience in using data-driven methods to evaluate tooling effectiveness and to prioritize improvements
• Experience with distributed systems debugging, profiling, or monitoring at scale
• Familiarity with ML frameworks (PyTorch, TensorFlow) or compiler infrastructure (LLVM, MLIR, TVM)