Senior AI Engineer, World Foundation Models

NVIDIA; Oregon (WI); On-site; USD 184,000 - 356,500; Full time

Benefits offered by this job

Equity options

Comprehensive benefits package

Job summary

NVIDIA is looking for a talented individual to advance the next generation of AI systems focused on dynamic video generation. This role includes conducting thorough research on model architectures to ensure human-centric quality and stability in video outputs.

The successful candidate will hold a PhD and have over 8 years of experience in ML, specifically with generative models. A competitive salary package ranging from $184,000 to $356,500 based on experience is included, along with equity and benefits.

Qualifications

• 8+ years of applied research experience in vision, graphics, or adjacent ML domains.
• 3+ years designing, training, and evaluating generative models for image/video/audio.
• Strong hands-on experience with large models in multi-GPU environments.

Responsibilities

• Research and implement model architecture changes for video generation fidelity.
• Improve training and inference efficiency through architectural techniques.
• Translate research results into robust implementations and demos.

Skills

Python

PyTorch

C++

CUDA

Deep Learning

Generative Models

Education

PhD in Computer Science, Graphics, Computer Engineering, or related field

Job description

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.

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 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.

What We Need To See

• 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.

Ways To Stand Out From The Crowd

• 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.

Salary: Level 4: 184,000 USD – 287,500 USD and Level 5: 224,000 USD – 356,500 USD, based on location and experience. Eligible for equity and a comprehensive benefits package.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal‑opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.