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

PyTorch

JAX

LLMs

VLMs

VLAs

DiTs

Transformers

Attention Mechanisms

Diffusion Models

Autoregressive Models

VAE

GAN

Retrieval-Augmented Generation

Neural Rendering

Multi-Agent Systems

Reinforcement Learning

Model Distillation

Large-Scale Training

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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