Research Scientist Intern, PyTorch On-Device (PhD)

Lensa is a career site that helps job seekers find great jobs in the US. We are not a staffing firm or agency. Lensa does not hire directly for these jobs, but promotes jobs on LinkedIn on behalf of its direct clients, recruitment ad agencies, and marketing partners. Lensa partners with DirectEmployers to promote this job for META. Clicking "Apply Now" or "Read more" on Lensa redirects you to the job board/employer site. Any information collected there is subject to their terms and privacy notice. **Summary** PyTorch is Meta's deep learning framework for fast, flexible AI/ML experimentation used across industry and backing all of Meta's ML workloads. More details at https://pytorch.org/Our team brings PyTorch to edge devices through the use of compilers, an optimized runtime, and leveraging unique mobile hardware (CPU, GPU, NPU, DSP) for inference and training.Team scope:- Develop ExecuTorch as the PyTorch solution for on-device AI- Partner with Reality Labs to run AI on AR/VR hardware- Partner with Meta family of apps for running AI on iOS and Android- Partner with hardware vendors on high-performance AI kernels- Provide on-device AI inference, feature stores, benchmarking, and model deliveryOur internships are twelve (12\) to twenty-four (24\) weeks long and we have various start dates throughout the year. **Required Skills** Research Scientist Intern, PyTorch On-Device (PhD) Responsibilities: * Develop new or apply existing performance techniques to on-device AI. * Explore quantization, sparsity, and model/software co-design as solutions. * Apply knowledge and research to advance the state-of-the-art in on-device machine learning frameworks. * Collaborate with users and developers of PyTorch and ExecuTorch to enable new use cases inside and outside Meta. **Minimum Qualifications** Minimum Qualifications: * Currently has, or is in the process of obtaining, PhD degree in the field of Computer Science or a related STEM field * Experience in ML compilers, sparsity, quantization, kernel development, or similar as applied to on-device and highly-constrained environments * Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment **Preferred Qualifications** Preferred Qualifications: * Experience working on other AI/ML optimized runtime stacks * Experience with performance optimization of machine learning models for on-device inference * Intent to return to degree program after the completion of the internship/co-op * Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, MLSys, ASPLOS, PLDI, CGO, PACT, ICML, or similar * Experience working and communicating cross functionally in a team environment **Public Compensation** $7,650/month to $12,134/month \+ 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. If you have questions about this posting, please contact support@lensa.com