Software Engineer, Generative-AI - New College Grad 2025

Details

At NVIDIA, we're not just building the future—we're generating it. Our Cosmos generative AI engineering team is pushing the boundaries of what's possible across multimodal learning, video generation, synthetic data, and intelligent simulation. We welcome hard-working engineers and applied scientists with deep experience in generative modeling to help define the next era of AI computing.

Responsibilities

• Design, post-train, and optimize novel world models (e.g., diffusion video models, VLMs, VLAs) for Physical AI applications.
• Contribute to highly-collaborative development on large-scale training infrastructure, high-efficiency inference pipelines, and scalable data pipelines.
• Work with teams in research, software, and product to bring world models from idea to deployment.
• Collaborate on open-source and internal projects, author technical papers or patents, and mentor junior engineers.
• Prototype rapidly and iterate on experiments across cutting-edge AI domains, including text-to-image/video generation, reinforcement learning, reasoning, and foundation models.
• Design and implement model distillation algorithms for size reduction and diffusion step optimization. Profile and benchmark training and inference pipelines to achieve production-ready performance requirements.

Requirements

• Pursuing BS, MS, or PhD in Computer Science, Machine Learning, Applied Math, Physics, or a related field (or equivalent experience).
• Proficiency in PyTorch, JAX, or other deep learning frameworks is a must.
• Expertise in one or more: diffusion models, auto-regressive models, VAE/GAN architectures, retrieval-augmented generation, neural rendering, or multi-agent systems.
• Intimate familiarity with all variants of attention mechanisms, as models are predominantly built on transformer architectures.
• Hands-on experience with large-scale training (e.g., ZeRO, DDP, FSDP, TP, CP) and data processing (e.g., Ray, Spark).
• Production-quality software engineering skills in Python.

Ways to Stand Out

• Familiarity with high-performance computing and GPU acceleration.
• Contributions to influential open-source libraries or conference publications (NeurIPS, ICML, CVPR, ICLR).
• Experience working with multimodal data (e.g., vision-language, VLA, audio).
• Prior work with NVIDIA GPU-based compute clusters or simulation environments.

Benefits

You will be eligible for equity and benefits. NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer.