Senior AI Researcher - World Foundation Models

About the role

NVIDIA is seeking a researcher to join our team in advancing world foundation models for video generation, focusing on human-centric quality. This role involves researching, implementing, and validating model architecture and algorithm changes to improve video generation fidelity.

Responsibilities

• Research, implement, and validate model architecture and algorithm changes that improve video generation fidelity, with emphasis on human-centric quality.
• Explore and prototype improvements across spatial multimodal modeling, modality alignment, flow-based or diffusion-based video generation, and neural rendering-inspired representations to improve controllability and long-horizon consistency.
• Improve training and inference efficiency through architectural and post-training techniques (compute/memory optimizations, distillation, pruning, and compression).
• Define model training objectives that improve sim-to-real and real-to-sim generalization, especially for human motion, contact, and interaction dynamics across real-world and synthetic/simulation data.
• Develop detailed, domain-specific benchmarks for evaluating world foundation models, especially generation and understanding world models that reason about video, simulation, and physical environments.
• Translate research results into robust implementations like training code, production-grade checkpoints, model integrations, and demos that clearly showcase capability gains across teams.

Requirements

• PhD in Computer Science, Graphics, Computer Engineering, or a closely related field (or equivalent experience).
• 8+ years of applied research and/or industry experience in vision, graphics, or adjacent ML domains or similar area.
• 3+ years of direct experience designing, training, and evaluating generative models for image/video/audio, with strong fundamentals in modern deep learning.
• Hands-on experience improving generative models with a focus on perceptual quality and temporal stability, especially for generating humans.
• Advanced proficiency in Python, PyTorch, C++, and CUDA with strong research-engineering practices (reproducibility, testing, profiling, experiment tracking).
• Experience training and debugging large models in multi-GPU and/or multi-node environments and distributed training workflows.
• PRACTICAL knowledge of inference/runtime bottlenecks and optimization techniques.
• Strong “eye for quality” and interest in diagnosing visual artifacts (sharpness, texture detail, temporal stability, etc.) using perceptual metrics, human preference signals, or learned evaluators.

Qualifications

• Proven track record in related research, including publications in top conferences (e.g., NeurIPS, CVPR, ICLR), with clear evidence of impact on model quality or robustness.
• Experience using agentic workflows, and AI coding companions, to accelerate research and production development, including code generation, debugging, test creation, experiment automation, benchmark development, documentation, and large-codebase navigation.

Skills

• Strong background in computer science, graphics, or machine learning.
• Experience with deep learning frameworks such as PyTorch and TensorFlow.
• Knowledge of computer vision, natural language processing, and reinforcement learning.
• Ability to develop and evaluate complex models for video generation.
• Experience with distributed training and optimization techniques.

Benefits

Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family here. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is $184,000 - $287,500 for Level 4, and $224,000 - $356,500 for Level 5. You will also be eligible for equity and benefits.

Pay

Base salary range: $184,000 - $287,500 for Level 4, and $224,000 - $356,500 for Level 5.

Schedule

Full-time.