Research Scientist Intern, AI & System Co-Design (PhD)
Meta
Research Scientist Intern, AI & System Co-Design (PhD)
Job Description
The AI System SW/HW Co-design team’s mission is to explore, develop, and help productize high-performance software and hardware technologies for AI at datacenter scale. We achieve this via concurrent design, performance projection, and optimization of many aspects of the system such as models, algorithms, numerics, performance, and AI hardware including compute, networking, and storage. We drive the AI HW roadmap at Meta and ensure our existing and future AI workloads and software are well optimized and suited for new infrastructure. The team works across HW types (GPUs, ASICs), workload types (Recommendation Models, LLM, LDM) and workloads (Training & Inference). We’re a diverse group of problem solvers driven by a culture of experimentation and innovation. As a Research Scientist Intern, you will be a key member of a team of innovators, working on leading AI workloads and distributed systems, and developing architectures to enable the future of AI SW/HW co-design. Our team at Meta AI offers twelve (12) to sixteen (16) weeks long internships and we have various start dates throughout the year. To learn more about our research, visit https://ai.facebook.com.
Locations
- Menlo Park, CA, USA
Salary
Estimated Salary Rangemedium confidence
8,000,000 - 12,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- AI SW/HW Co-designintermediate
- Concurrent Designintermediate
- Performance Projectionintermediate
- System Optimizationintermediate
- AI Hardware Designintermediate
- Compute Systemsintermediate
- Networkingintermediate
- Storage Systemsintermediate
- AI HW Roadmap Developmentintermediate
- Workload Optimizationintermediate
- GPU Developmentintermediate
- ASIC Designintermediate
- Recommendation Modelsintermediate
- Large Language Models (LLM)intermediate
- Latent Diffusion Models (LDM)intermediate
- AI Trainingintermediate
- AI Inferenceintermediate
- Distributed Systemsintermediate
- AI Architecturesintermediate
- Problem Solvingintermediate
- Experimentationintermediate
- Innovationintermediate
Required Qualifications
- Currently has, or is in the process of obtaining a PhD degree in the field of Computer Science or a related STEM field Knowledge of Hardware Architecture and Distributed systems with interest in one or more of High Performance Computing, Numerics, Performance, and AI hardware including compute, networking, and storage 2+ years experience in one or more of High Performance Computing, Numerics, Performance and AI hardware including compute, networking and storage Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment Track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as MICRO, ISCA, HPCA, ASPLOS, ATC, SOSP, OSDI, MLSys or similar Experience or knowledge in developing and debugging in C/C++, Python and/or PyTorch Experience driving original scholarship in collaboration with a team Experience leading a team in solving analytical problems using quantitative approaches Experience in theoretical and empirical research and for answering questions with research Experience communicating research for public audiences of peers Experience working and communicating cross functionally in a team environment Intent to return to the degree program after the completion of the internship/co-op (experience, 2 years)
Responsibilities
- Lead and support research that accelerates ML applications over one or more of software, system and accelerator architectures, optimizing training and/or inference of next generation AI workloads here at Meta. Work towards long-term ambitious research goals, while identifying intermediate milestones. Lead and collaborate on research projects with other researchers and engineers across diverse disciplines. Communicate research agenda, progress and results. Influence progress of relevant research communities by producing publications.
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Research Scientist Intern, AI & System Co-Design (PhD)
Meta
Research Scientist Intern, AI & System Co-Design (PhD)
Job Description
The AI System SW/HW Co-design team’s mission is to explore, develop, and help productize high-performance software and hardware technologies for AI at datacenter scale. We achieve this via concurrent design, performance projection, and optimization of many aspects of the system such as models, algorithms, numerics, performance, and AI hardware including compute, networking, and storage. We drive the AI HW roadmap at Meta and ensure our existing and future AI workloads and software are well optimized and suited for new infrastructure. The team works across HW types (GPUs, ASICs), workload types (Recommendation Models, LLM, LDM) and workloads (Training & Inference). We’re a diverse group of problem solvers driven by a culture of experimentation and innovation. As a Research Scientist Intern, you will be a key member of a team of innovators, working on leading AI workloads and distributed systems, and developing architectures to enable the future of AI SW/HW co-design. Our team at Meta AI offers twelve (12) to sixteen (16) weeks long internships and we have various start dates throughout the year. To learn more about our research, visit https://ai.facebook.com.
Locations
- Menlo Park, CA, USA
Salary
Estimated Salary Rangemedium confidence
8,000,000 - 12,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- AI SW/HW Co-designintermediate
- Concurrent Designintermediate
- Performance Projectionintermediate
- System Optimizationintermediate
- AI Hardware Designintermediate
- Compute Systemsintermediate
- Networkingintermediate
- Storage Systemsintermediate
- AI HW Roadmap Developmentintermediate
- Workload Optimizationintermediate
- GPU Developmentintermediate
- ASIC Designintermediate
- Recommendation Modelsintermediate
- Large Language Models (LLM)intermediate
- Latent Diffusion Models (LDM)intermediate
- AI Trainingintermediate
- AI Inferenceintermediate
- Distributed Systemsintermediate
- AI Architecturesintermediate
- Problem Solvingintermediate
- Experimentationintermediate
- Innovationintermediate
Required Qualifications
- Currently has, or is in the process of obtaining a PhD degree in the field of Computer Science or a related STEM field Knowledge of Hardware Architecture and Distributed systems with interest in one or more of High Performance Computing, Numerics, Performance, and AI hardware including compute, networking, and storage 2+ years experience in one or more of High Performance Computing, Numerics, Performance and AI hardware including compute, networking and storage Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment Track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as MICRO, ISCA, HPCA, ASPLOS, ATC, SOSP, OSDI, MLSys or similar Experience or knowledge in developing and debugging in C/C++, Python and/or PyTorch Experience driving original scholarship in collaboration with a team Experience leading a team in solving analytical problems using quantitative approaches Experience in theoretical and empirical research and for answering questions with research Experience communicating research for public audiences of peers Experience working and communicating cross functionally in a team environment Intent to return to the degree program after the completion of the internship/co-op (experience, 2 years)
Responsibilities
- Lead and support research that accelerates ML applications over one or more of software, system and accelerator architectures, optimizing training and/or inference of next generation AI workloads here at Meta. Work towards long-term ambitious research goals, while identifying intermediate milestones. Lead and collaborate on research projects with other researchers and engineers across diverse disciplines. Communicate research agenda, progress and results. Influence progress of relevant research communities by producing publications.
Tags & Categories