Research Scientist Intern, On-Device AI Model Optimization (PhD)

Meta; Menlo Park, Burlingame (CA, CA); Vor Ort; USD 55.000 - 83.000; Vollzeit

Zusammenfassung

Meta Reality Labs seeks interns to advance AR/VR machine learning models optimized for on-device deployment. You will develop efficient, real-time models for vision, speech, NLP, and multimodal AI, collaborating with hardware teams to bring ideas to reality.

Ideal candidates are pursuing a PhD in CS or EE, have work authorization, a track record of ML research and first-author publications, and experience with LLMs or multimodal reasoning models.

Qualifikationen

• Pursuing a PhD in CS, EE, or related field.
• Experience building ML models for AR/VR.
• Strong programming and deep learning framework skills.
• First-author publications at top ML/AI conferences.
• Experience training and running inference on LLMs and multimodal models.
• Familiarity with model optimization techniques for on-device deployment.
• Proven research and software engineering through internships or GitHub.

Aufgaben

• Develop efficient ML models for AR/VR on-device.
• Collaborate with domain experts and hardware teams.
• Publish research and contribute to codebases.
• Prototype ideas using DL frameworks.

Kenntnisse

ML solutions

On-device ML

Multimodal ML

Publications

Python

DL frameworks

GitHub

Ausbildung

PhD (pursuing) in CS/EE or related field

Tools

GitHub

Jobbeschreibung

Reality Labs advances Meta's vision for virtual reality (VR) and augmented reality (AR). Delivering compelling experiences on AR/VR devices requires innovation and co-design across the full technology stack, from algorithms to custom silicon. Our teams push the state of the art in computer vision, speech, virtual assistants, machine learning, mixed reality, graphics, displays, sensors, and human body tracking.

We are seeking interns with a background in developing efficient machine learning models for AR/VR applications, including computer vision, speech, sensor fusion, natural language processing (NLP), and multimodal AI. Our team develops high-performing models within tight compute, memory, and power constraints, using optimization techniques such as sparsity, quantization, compression, neural architecture search, and tensor decomposition. Ideal candidates will have practical experience building real-time models that maintain high accuracy under on-device deployment constraints.

In this role, you will gain experience across the full stack, from user experiences and algorithms to hardware execution. You will collaborate with domain experts to understand application challenges and develop state-of-the-art neural networks to address them, then partner with software and hardware teams to deploy these solutions on-device.

Our internships range from twelve (12) to twenty-four (24) weeks, with start dates throughout the year.

• Currently holds or is pursuing a PhD in Computer Science, Electrical Engineering, or a related field
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
• Experience developing machine learning solutions
• Programming experience and experience using deep learning frameworks to prototype ideas
• A track record of first-author publications at top-tier machine learning or AI conferences, such as NeurIPS, ICML, ICLR, ACL, AAAI, or similar venues
• Experience training and running inference with LLMs, multimodal models, or reasoning models
• Experience with one or more model optimization techniques, such as quantization, pruning, distillation, parameter-efficient fine-tuning (PEFT), or speculative decoding, for cloud or on-device AI deployment
• Demonstrated research and software engineering experience through internships, coding competitions, or contributions to open-source repositories, such as those hosted on GitHub