Research Intern – Video World Models (Research & ML Systems)

About the role

We are seeking an exceptional Research Intern to join our core team in building the next generation of interactive Video World Models. While traditional generative AI focuses on generating passive pixels (e.g., text-to-video), our mission is fundamentally more ambitious: we are building foundational "World Models" that inherently understand physics, causality, action spaces, and complex dynamics directly from internet-scale data. Our goal is to train models that can simulate and "dream" complex virtual worlds, allowing users and agents to explore and interact with them in real time.

Responsibilities

• Arcitect & Scale Foundation Models: Design, train, and scale state-of-the-art interactive world models (combining Diffusion, Autoregressive Transformers, VAEs, LLMs, VLMs) on massive video datasets.
• Push the Boundaries of ML Systems: Architect highly scalable distributed training pipelines, utilizing advanced model and data parallelism to train massive models efficiently on large-scale computing clusters.
• Optimize for Efficiency: Profile and optimize model architectures to break through memory and compute bottlenecks.
• Write high-performance, custom hardware kernels to maximize Model FLOPs Utilization (MFU) and enable real-time, low-latency inference.

Requirements

• Academic Excellence: Currently pursuing a PhD (or Master’s degree with a truly exceptional research/engineering track record) in Computer Science, Machine Learning, Computer Architecture, or a related field.
• Engineering Skills: Exceptional, production-level coding proficiency in Python or other languages. Background in competitive programming is a great plus.
• AI Infrastructure & Scaling: Experience with modern AI infrastructure stack and large-scale machine learning systems, such as PyTorch FSDP, Megatron, etc. Experience with GPU kernels using CUDA and/or Triton is a great plus.
• Deep Generative Expertise: Thorough theoretical and practical understanding of modern generative paradigms (Diffusion, Vision Transformers, Autoregressive sequence modeling, discrete tokenization/VAEs).
• Top-Tier Publication Record: First-author publications in top-tier AI venues (NeurIPS, ICLR, ICML, CVPR, ICCV) OR premier ML Systems venues (MLSys, OSDI, ASPLOS).

Qualifications

Location: State(s) - US-California-Palo Alto

The expected base pay range for this position in the location(s) listed above is $80,168.40 to $124,800.00 per year. Actual pay may vary depending on job-related knowledge, skills, and experience.

This position will be eligible for 1 hour of paid sick leave for every 30 hours worked and up to 13 paid holidays throughout the calendar year.

Subject to the terms and conditions of the applicable plans then in effect, full-time interns are also eligible to enroll in the Company-sponsored medical plan.

Skills

As a Research Intern, you should have a strong foundation in computer science, machine learning, and deep learning. You should also have excellent problem-solving skills and be able to work independently and collaboratively.

Benefits

Full-time interns are eligible to enroll in the Company-sponsored medical plan.

Pay

The expected base pay range for this position in the location(s) listed above is $80,168.40 to $124,800.00 per year. Actual pay may vary depending on job-related knowledge, skills, and experience.

Schedule

This position will be eligible for 1 hour of paid sick leave for every 30 hours worked and up to 13 paid holidays throughout the calendar year.