**Summary:**

Meta is seeking a Software Engineer to join our Systems ML Engineering team, focused on building and optimizing the machine learning infrastructure that powers Meta's products at massive scale. In this role, you will design and develop high-performance ML systems, working across the full stack from model training and inference pipelines to hardware-aware optimizations. You will collaborate with researchers, platform engineers, and product teams to accelerate ML workloads and improve the efficiency of AI infrastructure that serves billions of users.

**Required Skills:**

Software Engineer, Systems ML Responsibilities:

1. Design, build, and optimize large-scale ML training and inference systems, including distributed computing frameworks and hardware-accelerated pipelines

2. Develop and maintain high-performance ML infrastructure components in C++ and Python, ensuring reliability, scalability, and low-latency execution

3. Identify and resolve performance bottlenecks across the ML stack using profiling, instrumentation, and benchmarking tools

4. Architect and evaluate trade-offs in ML system design, including memory bandwidth, compute utilization, and I/O throughput

5. Partner with research and product teams to translate ML model requirements into efficient infrastructure solutions

6. Write automated tests covering expected behaviors, failure modes, and error paths for ML infrastructure components, and build monitoring and alerting for production anomalies

7. Contribute to staged rollout strategies using feature flagging and experimentation frameworks to safely deploy ML system changes

8. Produce accurate technical documentation when introducing new ML infrastructure features or updating existing systems

9. Participate in on-call rotations to investigate and mitigate production incidents affecting ML serving systems, and contribute detailed retrospectives

10. Provide constructive code review feedback to other engineers and contribute to engineering programs that improve the health and quality of the ML infrastructure codebase

**Minimum Qualifications:**

Minimum Qualifications:

11. 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

12. 2+ years of experience in software engineering with a focus on machine learning systems, AI infrastructure, or high-performance computing

13. Experience developing or optimizing ML training or inference pipelines using frameworks such as PyTorch, TensorFlow, or equivalent

14. Experience with distributed computing architectures and large-scale systems design for ML workloads

15. Experience programming in C++ and Python for performance-critical systems

16. Experience using profiling and performance analysis tools to identify and resolve bottlenecks in ML or compute-intensive systems

**Preferred Qualifications:**

Preferred Qualifications:

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

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

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

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

21. Experience with ML compiler technologies such as MLIR, LLVM, TVM, XLA, or IREE

22. Experience with GPU programming using CUDA, ROCm, or equivalent hardware accelerator kernel development

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

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

25. Experience optimizing large-scale ranking or recommendation model inference on AI accelerator hardware such as GPUs or TPUs

26. Experience with hardware-software co-design, including numerics optimization and SIMD or vectorization techniques

**Public Compensation:**

$121,992/year to $181,000/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.