Senior AI Researcher – World Foundation Models

🕒 Yesterday

🏄 California, Oregon, +1 more states – Remote

🏄 California – Remote 🌲 Oregon – Remote ☕ Washington – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

🧠 AI Research Scientist

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• 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.

🏖️ Benefits

• Equity • Benefits