Senior Generative AI Research Engineer at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

Requirements

Minimum 8 years industry experience or 5+ years research/postdoc in building and deploying generative AI systems
Proficiency in PyTorch, JAX, or other deep learning frameworks
Expertise in one or more of: LLMs, coding agents, diffusion models, autoregressive models, VAE/GAN architectures, retrieval-augmented generation, neural rendering, or multi-agent systems
Intimate familiarity with all variants of transformer attention mechanisms
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
MS or PhD or equivalent experience in Computer Science, Machine Learning, Applied Math, Physics, or a related field
12+ years of relevant software development experience

Responsibilities

Design and post-train foundation models (LLMs, VLMs, VLAs, and DiTs) for real-world 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 and iterate rapidly on experiments across cutting-edge AI domains, including agentic systems, reinforcement learning, reasoning, and video generation
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

Skills

Key technologies and capabilities for this role

PyTorchJAXLLMsVLMsVLAsDiTsTransformersAttention MechanismsDiffusion ModelsAutoregressive ModelsVAEGANRetrieval-Augmented GenerationNeural RenderingMulti-Agent SystemsReinforcement LearningModel DistillationLarge-Scale Training

Questions & Answers

Common questions about this position

What is the salary range for this position?

The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 425,500 USD for Level 6, determined based on location, experience, and pay of employees in similar positions.

Is this a remote position or does it require working in an office?

This information is not specified in the job description.

What skills and experience are required for this role?

Candidates need minimum 8 years industry or 5+ years research/postdoc experience building generative AI systems, proficiency in PyTorch, JAX, or other deep learning frameworks, expertise in foundation models like LLMs or diffusion models, familiarity with transformer attention mechanisms, hands-on experience with large-scale training and data processing, production-quality Python software engineering skills, and MS/PhD or equivalent in a relevant field with 12+ years software development experience.

What is the team culture like at NVIDIA's Cosmos generative AI team?

The team is highly collaborative, working with research, software, and product teams to bring world models from idea to deployment, and emphasizes open-sourcing products, authoring technical papers or patents, and mentoring junior engineers.

What makes a candidate stand out for this Senior Generative AI Research Engineer role?

Stand out with familiarity in high-performance computing and GPU acceleration, contributions to influential open-source libraries or conference publications (NeurIPS, ICML, CVPR, ICLR), experience with multimodal data like vision-language or VLA, and prior work with NVIDIA GPU-based compute clusters or simulation environments.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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