**Summary:**

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, advancing ML accelerator tooling by leveraging Meta's full-stack ownership from silicon specs to fleet observability. In this role, you will be a senior technical contributor responsible for designing and building 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.

**Required Skills:**

Software Engineer, MTIA SW Tooling Engineer Responsibilities:

1. Own the technical vision and roadmap for key areas of MTIA's developer tooling ecosystem, focusing on debugging, workload error analysis, and product / fleet reliability

2. Design and develop debugging tools — including graph-mode debugging, kernel-level diagnostics, and multi-rank fault isolation

3. Contribute to overall MTIA SW tooling infrastructure — enabling profiling, performance debugging, memory sanitization, and reliability analysis for MTIA training and inference workloads

4. Collaborate closely with MTIA compiler, runtime, kernel, and hardware teams to integrate tooling hooks throughout the MTIA software stack

5. Drive AI-native tooling approaches by leveraging automation and LLM-guided diagnostics to improve developer productivity and reduce time-to-root-cause

6. Partner with internal product teams across advertising, recommendations, and generative AI to understand developer pain points and prioritize tooling investments

7. Advise on tooling best practices, debugging methodologies, and systems-level analysis for accelerator software

8. communicate architectural decisions clearly through design documents and cross-team reviews

**Minimum Qualifications:**

Minimum Qualifications:

9. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

10. 6+ years of experience in systems software engineering, performance engineering, developer tooling, or a closely related field

11. Experience building debugging, profiling, or diagnostic tools for complex software/hardware systems

12. Proficiency in C++ and Python, including low-level systems programming and scripting for tool automation

13. Experience working across multiple layers of a system stack (compiler, runtime, OS/driver, hardware)

14. Experience leading the technical design and delivery of tooling or infrastructure projects from inception through production deployment

15. Experience using data-driven methods and experimentation to evaluate and validate tooling effectiveness and systems performance improvements

**Preferred Qualifications:**

Preferred Qualifications:

16. Familiarity with ML framework internals (PyTorch graph execution, torch.compile, operator dispatch) and AI compiler stacks (MLIR, LLVM, TVM, Triton)

17. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

18. Experience with accelerator ecosystems (GPU/CUDA, TPU, custom ASICs) including performance profiling, memory analysis, and runtime debugging using their toolchains (cuda-gdb, nsight-compute, nsight-systems, cuda-memcheck)

19. Demonstrated cross-stack debugging ability, including Linux kernel and driver-level debugging, with capacity to trace issues across application, OS, and hardware boundaries

20. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

21. Experience with distributed systems debugging or profiling (multi-device, multi-node/multi-rank)

22. Experience with Linux debugging and profiling infrastructure (gdb, perf, eBPF, ftrace, coredump analysis, hardware performance counters) and familiarity with binary formats and debugging metadata (ELF/DWARF)

23. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

24. 7+ years of experience in systems software, developer tooling, or accelerator software development (or equivalent with advanced degree)

25. Track record of building developer tools adopted by large engineering populations, ideally with contributions to open-source projects (gdb, LLVM sanitizers, Valgrind, Triton, etc.)

**Public Compensation:**

$183,997/year to $257,000/year + bonus + equity + benefits

**Industry:** Internet

**Equal Opportunity:**

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.