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

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

Job summary

Meta is seeking a Research Scientist in AI & Systems Co-Design (PhD) to advance GenAI efficiency from model to hardware at datacenter scale. You will collaborate across architecture, compiler, and runtime teams to co-design deployment techniques and optimized ML kernels for accelerators.

The role requires a PhD (or equivalent) with strong publication track record, deep Python proficiency, and experience with AI frameworks, CNNs/Transformers/LLMs.

Qualifications

• Bachelor's degree completed before joining Meta
• PhD in CS/EE or related field, or Master's with 3+ years of experience
• Proven research in hardware-aware model enablement or AI system performance modeling
• Hands-on AI hardware architecture experience and on-device mapping development
• Theoretical and practical knowledge of AI models (CNNs, Transformers, LLMs)
• Experience in system-level performance analysis and benchmarking
• Proficient in Python and at least one major AI framework
• Track record of publishing research and communicating results to stakeholders

Responsibilities

• Explore and optimize parallelisms and compute efficiency for GenAI systems
• Co-design model deployment techniques for scalable hardware efficiency
• Benchmark and model performance across AI workloads for future hardware and runtime feedback
• Prototype and productionize optimized ML kernels for accelerators
• Influence the hardware roadmap for Meta's AI accelerators
• Lead cross-functional initiatives across engineering groups
• Guide AI hardware requirements and software stack design for future workloads

Skills

Python

AI framework

Research

System optimization

Education

Bachelor's degree in CS/Engineering

PhD in CS or EE

Master's with 3+ years experience

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 productization 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), hardware architecture (ISCA, ASPLOS), ML (NeurIPS, ICML, ICLR) and supercomputing (SC, ICS).

Research 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 systems
• Innovate and co-design novel model deployment techniques for sustained scaling and hardware efficiency during GenAI serving
• Benchmark, 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 teams
• Explore, prototype and productionize highly optimized ML kernels to unlock full potential of current and future accelerators for Meta’s AI workloads
• Influence the hardware roadmap of Meta’s custom AI accelerators
• Lead cross-functional initiatives spanning multiple engineering organizations to drive high-impact technical milestones
• Guide 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 systems

Minimum 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 Meta
• PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related technical field, OR a Master's degree with 3+ years of relevant industry experience
• Proven research experience in one or more of the following areas: hardware-aware model enablement, performance modeling of AI systems or prevailing accelerators/silicon architectures
• Hands‑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., CNNs, Transformers, LLMs, Diffusion models)
• Experience in system-level performance analysis, profiling, and benchmarking of AI workloads
• In‑depth experience of Python and experience with at least one major AI framework
• Track record of publishing research papers at peer-reviewed conferences or journals, and experience communicating technical results to cross-functional stakeholders

Preferred Qualifications:

• Experience with deploying AI agents/prevalining techniques for increased efficiency
• Experience or knowledge of training/inference of large-scale deep learning models
• Familiarity with low-level programming for specialized hardware (e.g., CUDA, HIP, Triton) or hardware description languages (HDL)
• Experience or knowledge of distributed ML systems and algorithm development
• Experience or knowledge of either Generative AI models such as LLMs/LDMs or Ranking & Recommendation models such as DLRM or equivalent

About 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 see at [e-mail].

$122,000/year to $181,000/year + bonus + equity + benefits

Individual 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.