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

$117,000 - $173,000/Yr

Meta - Redmond, WA

Full-time - Entry Level

Redmond, WA

5,001-10,000 employees

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About the position

Meta Reality Labs is seeking a Research Scientist to join its Research & Development teams, focusing on AI Infrastructure and models. The role aims to develop innovative solutions for compute and power-efficient training and on-device inference of vision and language models for augmented and virtual reality applications. The ideal candidate will leverage their expertise to address critical challenges in Reality Labs, contributing to the advancement of intelligent ML systems that enhance Meta's products and experiences.

Responsibilities

• Apply relevant AI infrastructure, AI algorithms, and hardware acceleration techniques to build and optimize intelligent ML systems.
• Develop state-of-the-art model compression and scalability techniques using numerics, pruning, and distillation.
• Optimize models on hardware to achieve the best performance under 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 and 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 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

• Competitive salary with bonus and equity options.
• Comprehensive health insurance coverage.
• 401k retirement savings plan with matching contributions.
• Paid time off and holidays.
• Flexible work hours and remote work options.