NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC , VISUAL, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers. You will work closely with industry sales, developer relationship managers and product teams in the hiring position.
What you’ll be doing:
Drive development, and optimization of Reinforcement Learning algorithms and infrastructure for Large Language Models and multimodal models.
Develop and enable prompt open source models support in NVIDIA RL and post-training frameworks.
Collaborate with internal research and engineering teams to adapt and validate state-of-the-art RL methods and optimizations to NVIDIA platform.
Improve Reinforcement Learning initiatives and engagements with customers, providing technical guidance on integrating NVIDIA RL technologies into their AI workflows.
Develop and maintain reusable toolchains, experiment management workflows, and technical documentation to accelerate both internal and customer-facing projects.
What we need to see:
MS or PhD in Computer Science, Artificial Intelligence, Mathematics, or related fields, with solid foundations in algorithms and programming.
5+ years of experience (including research) in Reinforcement Learning, Large Language Model training, or multimodal learning.
Proficient in PyTorch and familiar with RL training frameworks and workflows.
Strong engineering skills with experience in distributed training, task orchestration, or evaluation pipelines.
Ability to work independently with minimal day-to-day direction, and willingness to conduct exploratory experiments on frontier problems.
Desire to be involved in multiple diverse and innovative projects.
Outstanding verbal and written communication skills.
Ways to stand out from the crowd:
Experience with RLHF, GRPO, DPO, or other alignment and post-training methods for LLMs.
Experience with scale-out HPC or cloud architectures for large-scale model training.
CUDA optimization or GPU performance tuning experience.
Experience with agentic AI systems, code generation models, or multimodal RL.
Publications in top-tier venues in RL, NLP, or multimodal learning.
With competitive salaries and a generous benefits package, we are widely considered to be one of the world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you.
Skills Required
- MS or PhD in Computer Science, Artificial Intelligence, Mathematics, or a related field
- Solid foundations in algorithms and programming
- 5+ years of experience, including research, in Reinforcement Learning, Large Language Model training, or multimodal learning
- Proficiency in PyTorch
- Familiarity with reinforcement learning training frameworks and workflows
- Strong engineering skills with experience in distributed training, task orchestration, or evaluation pipelines
- Ability to work independently with minimal day-to-day direction
- Willingness to conduct exploratory experiments on frontier problems
- Outstanding verbal and written communication skills
- Experience with RLHF, GRPO, DPO, or other alignment and post-training methods for LLMs
- Experience with scale-out HPC or cloud architectures for large-scale model training
- CUDA optimization or GPU performance tuning experience
- Experience with agentic AI systems, code generation models, or multimodal reinforcement learning
- Publications in top-tier venues in reinforcement learning, NLP, or multimodal learning
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
