Senior AI Researcher – World Foundation Models

🕒 il y a 4 mois

🏄 California, Oregon, +1 états de plus – Distant

infoinfo

💵 $184 000 - $356 500 / an

⏰ Temps Plein

🟠 Senior

🧠 Chercheur en IA

🗣️🇺🇸🇬🇧 Anglais requis

D'où vient cette offre

Publiée sur la page carrières de NVIDIA, pas via un site d'emploi

Repérée par Remote Rocketship il y a 4 mois

Toujours ouverte sur le site de NVIDIA. Vérifiée il y a 2 heures.

Logo of NVIDIA

NVIDIA

10 000+ employés

Fondée en 1993

🏥 Santé

🏭 Fabrication

🤖 Intelligence artificielle

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA est une entreprise technologique de premier plan, spécialisée dans le calcul accéléré et l’intelligence artificielle (IA). NVIDIA est à l’avant‑garde des avancées en GPU (processeurs graphiques), cloud computing, centres de données et réalité virtuelle, avec un accent particulier sur les secteurs du gaming, de l’automobile, de la santé et de la robotique. Ses innovations, telles que NVIDIA Omniverse, transforment les processus numériques traditionnels en permettant des simulations haute fidélité et des tâches de rendu de pointe. Ses applications couvrent de nombreux secteurs, des véhicules autonomes avec NVIDIA DRIVE aux solutions de santé avec NVIDIA Clara, ainsi que des analyses et workflows pilotés par l’IA.

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.

🎯 Exigences

• 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.

🏖️ Avantages

• Equity • Benefits

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