Research Scientist, Systems ML - SW/HW Co-design (PhD)

$117,000 - $173,000/Yr

Meta - Sunnyvale, CA

Full-time - Entry Level

Sunnyvale, CA

5,001-10,000 employees

Web Search Portals, Libraries, Archives, and Other Information Services

About the position

The Research Scientist, Systems ML - SW/HW Co-design position at Meta focuses on developing innovative solutions for machine learning systems that enhance the performance and efficiency of virtual and augmented reality applications. The role involves applying AI infrastructure and algorithms to optimize models for real-time performance and power constraints, contributing to the advancement of Meta's products and experiences in the Reality Labs division.

Responsibilities

• Apply relevant AI infrastructure, AI algorithms and hardware acceleration techniques to build & optimize intelligent ML systems.
• Develop state-of-the-art model compression and scalability techniques using numerics, pruning, distillation, etc.
• Optimize models on hardware to achieve the best performance given various real-time latency and power constraints.
• Set goals related to project impact, AI algorithms, AI system design, and infrastructure/developer efficiency.
• Influence partners to deliver impact through thorough data-driven analysis.
• Define use cases and develop methodology & benchmarks to evaluate different approaches.
• Apply in-depth knowledge of how the ML infrastructure interacts with other systems.

Requirements

• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field.
• Currently has, or is in the process of obtaining a PhD in Computer Science, Electrical Engineering, or equivalent practical experience.
• Specialized experience in machine learning/deep learning domains such as model compression, hardware-aware model optimizations, or AI infrastructure.
• Experience developing AI-System infrastructure, AI algorithms, or AI hardware acceleration in C/C++ or Python.
• Must obtain work authorization in the country of employment at the time of hire.

Nice-to-haves

• Experience or knowledge of training/inference of large-scale AI models.
• Experience or knowledge of distributed systems or on-device algorithm development.
• Proven track record of achieving significant results demonstrated by grants, fellowships, patents, or publications at leading conferences.
• Demonstrated research and software engineering experience via internships or contributions in open source repositories.
• Experience working and communicating cross-functionally in a team environment.

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• 401(k) plan
• Paid holidays
• Paid time off
• Flexible scheduling
• Professional development opportunities
• Employee stock purchase plan
• Tuition reimbursement