Software Engineer, AI Co-design

Meta•Sunnyvale, CA

1d•$183,997 - $257,000

About The Position

Meta's Reality Labs Silicon team develops custom silicon for Virtual Reality and Augmented Reality devices, working across the stack from transistors and architecture to firmware and algorithms. The team is seeking a Software Engineer for its Research & Development teams to work on AI models, hardware acceleration, and related software systems. The role focuses on developing novel solutions for compute- and power-efficient training and on-device inference of vision and language models for AR, VR, and edge-device use cases. The position is available in multiple locations.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
PhD in Electrical Engineering, Computer Science, or equivalent experience.
Experience developing AI-system infrastructure, AI algorithms, or AI hardware acceleration in C/C++ or Python.

Nice To Haves

Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Experience working and communicating cross-functionally in a team environment.
Experience or knowledge of on-device algorithm development, including hardware-aware ML models and/or optimizing ML compilers for efficient deployment on AI accelerators.
Research and engineering experience demonstrated through an internship, work experience, coding competitions, or widely used contributions to open-source repositories such as GitHub.
Experience or knowledge of training or inference for large-scale AI models, including computer vision and/or large language models.
Experience with PyTorch, TensorFlow, or similar machine-learning toolsets.
Experience evaluating alternative system or algorithm designs by analyzing performance, power, and latency trade-offs to recommend a solution.
Experience or knowledge of architecting ML hardware accelerators and systems.
Ongoing AI skill development, such as prompt/context engineering or agent orchestration, and staying current with emerging AI technologies.
Experience implementing responsible and ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Track record of significant results demonstrated by grants, fellowships, patents, or publications at leading workshops, journals, or conferences such as ICLR, NeurIPS, CVPR, ACL, ICML, MLSys, ISCA, MICRO, DAC, or ASPLOS.

Responsibilities

Identify and solve multidisciplinary ML acceleration problems involving algorithms, network design, hardware architecture, and AR/VR use cases, including problems requiring novel approaches.
Collaborate with research scientists across hardware and software to solve co-design problems.
Co-design and invent novel ML accelerator and system architecture solutions, and facilitate integration of algorithms and software to use these enhancements.
Develop model compression and scalability techniques using methods such as numerics, pruning, and distillation.
Optimize models on hardware accelerators to meet real-time latency and power constraints.
Influence partners to adopt recommended solutions through data-driven analysis and clear communication of trade-offs.
Define use cases and develop methodologies and benchmarks to evaluate different approaches.
Apply in-depth knowledge of how ML acceleration interacts with surrounding systems.
Attend conferences, interpret papers, and stay current with ML acceleration research; contribute to patents and/or publications in peer-reviewed conferences and journals.