Senior AI Researcher - World Foundation Models
NVIDIA· Engineer, Sys SW
Hybrid (US-CA-Remote), Hybrid (US-WA-Remote), Hybrid (US-OR-Remote)$184k - $287.5kFull-timePosted 5mo ago
About the role
Senior AI research role focused on world foundation models for high-fidelity video generation, with emphasis on human appearance, motion, and action understanding. Research, validate, and productionize model improvements; collaborate with data, platform, and product engineering to translate research into robust, production-grade capabilities.
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.
Qualifications
- 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 using perceptual metrics, human preference signals, or learned evaluators.
Skills
Required:PythonPyTorchC++CUDAGenerative modelsVideo generationModel optimization
Benefits
- equity
- comprehensive benefits package
- base salary and location-based compensation
- benefits website: www.nvidiabenefits.com/
Last updated Jun 26, 2026. Interested? Apply on the company site.
About NVIDIA
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