Research Scientist, AI & Systems Co-Design (PhD)

Meta; Menlo Park (CA); On-site; USD 122,000 - 181,000; Full time

Benefits offered by this job

Equity compensation

Bonus program

Benefits package

Job summary

Meta is seeking a Research Scientist, AI & Systems Co-Design to explore and optimize parallelisms, compute efficiency, and distributed training/inference for GenAI and recommendation systems. The role emphasizes novel deployment techniques, kernel optimization, and cross-disciplinary collaboration to push AI workloads to scale with hardware-aware design.

The candidate will influence system, silicon, and runtime teams, driving performance modeling and empirical evaluation across accelerators,

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering or relevant field, or equivalent practical experience.
• PhD in Computer Science, Electrical Engineering, Applied Mathematics, or related field (completed or near completion).
• Experience in computer architecture, operating systems, ML systems and kernels, ML compilers, model-system co-design, performance modeling of AI systems.

Responsibilities

• Explore, co-design and optimize parallelisms, compute efficiency, distributed training/inference paradigms for GenAI and recommendation systems.
• Innovate and co-design model deployment techniques for scalable, hardware-efficient serving.
• Prototype and productionize optimized ML kernels for current/future accelerators.
• Guide AI hardware requirements and design focusing on system performance at silicon level.

Skills

Research experience

Model architectures knowledge

Python programming

Distributed ML systems

Performance modeling

Communication to stakeholders

Education

Bachelor's degree in CS/CE/Math or related field

PhD in CS/EE/Applied Math or related field (completed or near completion)

Tools

CUDA

HIP

Triton

HDL

Job description

Our teams’ mission is to explore, develop and help productionize high-performance software & hardware technologies for AI at datacenter scale. We achieve this via concurrent design and optimization of many aspects of the system from models and runtime all the way to the AI hardware, optimizing across compute, network and storage. The team invests significantly into model optimization on existing accelerator systems and guiding the future of models and AI HW at Meta. This drives improved performance, new model architectures and reduces cost of ownership for all key AI services at Meta: Recommendations and Generative AI. This is an exciting space that spans exploration and productionization, coupled with close collaborations with industry, academia, Meta’s Infrastructure and Product groups. Collaborating closely with product teams, the team's mode of operation is going from ideation and rapid prototyping, all the way to assisting productionization of high leverage ideas, working with many partner teams to bring learnings from prototype into production. In addition to the real-world impact on billions of users of the Meta products, our team members have won Best Paper Awards at prestigious conferences such as ISCA, ASPLOS, SOSP, and OSDI, with multiple papers selected for IEEE Micro Top Picks. We regularly publish in ICML, NeurIPS, SC, HPCA, NSDI, VLDB, MLSys, and more. Overall, our work largely corresponds to the research communities of systems in general and especially systems for ML (MLSys, SOSP, OSDI, SIGCOMM, NSDI), computer architecture (ISCA, ASPLOS, MICRO, HPCA), and ML (NeurIPS, ICML, ICLR). Learn more about our team from our website: https://aisystemcodesign.github.ioResearch Scientist, AI & Systems Co-Design (PhD) Responsibilities:Explore, co-design and optimize parallelisms, compute efficiency, distributed training/inference paradigms and algorithms to improve the scalability, efficiency, and reliability of GenAI and recommendation systemsInnovate and co-design novel model deployment techniques for sustained scaling and hardware efficiency during GenAI and recommendation model servingExplore, prototype and productionize highly optimized ML kernels to maximize the utilization and performance of current and future accelerators for Meta’s AI workloadsBenchmark, analyze, model, and project the performance of AI workloads against a wide range of what-if scenarios and provide early input to the design of future hardware, models, and runtime, giving crucial feedback to the architecture, compiler, kernel, modeling, and runtime teamsGuide Meta’s AI HW requirements and design focusing on performance at System and Silicon levels. Co-design and optimize our AI HW and related software stack for Meta’s future workloads, with technology pathfinding and evaluation of cutting-edge AI systemsLead cross-functional initiatives spanning multiple engineering organizations to drive high-impact technical milestonesMinimum Qualifications: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 MetaA PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related technical field. (Completed or near completion.)Proven research experience in one or more of the following areas: computer architecture, operating systems, ML systems and kernels, ML compilers, model-system co-design, performance modeling of AI systems, prevailing accelerators/silicon architectures, ML training algorithmsHands-on proficiency with end-to-end AI hardware architecture or on-device mapping algorithm development, encompassing logic, architecture, and optimizations for performance, power, and area (Power, Performance, and Area) (PPA)Theoretical background and practical experience with AI models (e.g., Transformers, LLMs, Diffusion models, CNNs, Recommendation Models)Experience in system-level performance analysis, profiling, and benchmarking of AI workloadsExperience in Python, including developing production-quality code or research prototypes and experience with at least one major AI frameworkTrack record of publishing research papers at peer-reviewed conferences or journals, and experience in communicating technical results to cross-functional stakeholdersPreferred Qualifications:Experience or knowledge of distributed machine learning systems and algorithm developmentExperience or knowledge of GenAI models, such as LLMs/LDMs or ranking and recommendation models, such as DLRM or equivalentExperience or knowledge of training/inference of large-scale deep learning modelsFamiliarity with low-level programming for specialized hardware (e.g., CUDA, HIP, Triton) or hardware description languages (HDL)Experience with deploying AI agents and prevailing techniques for increased efficiencyroven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferencesExperience working and communicating cross-functionally in a team environmentAbout Meta:Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.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 [e-mail].$122,000/year to $181,000/year + bonus + equity + benefitsIndividual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.