NVIDIA
AI
SeniorAIEngineer,WorldFoundationModels
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior AI Engineer, World Foundation Models at NVIDIA. Skills: World Foundation Models, Generative Models, Video Generation, Human Appearance, Motion, and Action Understanding, Deep Learning, PyTorch, Python, C++, CUDA. 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 vide”
What You'll Achieve.
Improve video generation fidelity; Improve controllability and long-horizon consistency; Improve training and inference efficiency; Improve sim-to-real and real-to-sim generalization; Ensure improvements translate into real performance and quality
Industry & Context.
Diagnosing visual artifacts
What They're Looking For.
Must Have
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 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 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, “eye for quality” and interest in diagnosing visual artifacts (sharpness, texture detail, temporal stability, etc. ) using perceptual metrics, human preference signals, or learned evaluators
Nice to Have
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
What You'll Do.
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
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
Define model training objectives that improve sim-to-real and real-to-sim generalization
especially for human motion
and interaction dynamics across real-world and synthetic/simulation data
domain-specific benchmarks for evaluating world foundation models
especially generation and understanding world models that reason about video
and physical environments
Translate research results into robust implementations like training code
production-grade checkpoints
and demos that clearly showcase capability gains across teams
How You'll Work.
Team & Collaboration
Work is delivered in close partnership with data, platform, and product engineering to ensure improvements translate into real performance and quality
Full Job Description
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA is building the next generation of AI systems that can perceive, reason about, and generate dynamic worlds. Our team advances world foundation models to enable high-fidelity, temporally stable video and world generation for Physical AI, simulation, and interactive experiences. This role operates at the applied-research boundary: developing and validating model improvements, then hardening them into production-grade checkpoints and recipes that teams can reliably build on. The technical focus is on human appearance, motion and action understanding. Progress is measured through disciplined experimentation, robust diagnostics, and repeatable side-by-side evaluation. Work is delivered in close partnership with data, platform, and product engineering to ensure improvements translate into real performance and quality. **What you 'll be doing:** * 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 t
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