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Full Stack Developer, AI and LLM - job 1 of 2

NVIDIA's Silicon Solutions Group is seeking a full-stack developer with AI/LLM expertise to help integrate AI into its data analysis and automation infrastructure. The solutions developed will support multiple critical large-scale automation initiatives. In this role, you will lead strategies and design of AI solutions to improve the efficiency of our existing and new automation workflows. The ideal candidate will combine technical expertise with hands-on experience to drive all AI planning, design, and implementation aspects. At NVIDIA, we strive for excellence, encourage innovation, and provide opportunities to explore new ways to succeed!

What You'll Be Doing:

  • Study and develop groundbreaking techniques in deep learning, graphs, machine learning, and data analytics, and perform in-depth analysis.

  • Collaborate with developers and cross-functional teams to identify current and emerging challenges.

  • Design and implement end-to-end generative AI solutions, specializing in Large Language Model (LLM) training, efficient deployment strategies, and sophisticated Retrieval-Augmented Generation (RAG) workflows.

What We Need to See:

  • MS (or equivalent experience) with 6+ years of software development; 2+ years relevant work experience in developing and deploying AI solutions

  • Proven full-stack development experience with a focus on improving application performance and user experience

  • Proficiency in Python, C++ programming, and Deep Learning frameworks

  • Ability to work independently and as part of a team

  • Motivated self-starter with strong analytical and debug skills

  • Ability to balance multiple simultaneous projects

  • Excellent verbal and written communication skills

Ways to Standout from the crowd:

  • Experience with CUDA programming and benchmarking and analyzing performance AI Agentic systems

  • Expertise in training, fine-tuning, and evaluating LLMs using popular frameworks such as TensorFlow or PyTorch

  • Proficiency in model deployment and optimization techniques for efficient inference on various hardware platforms

  • Experience with NVIDIA GPUs and software libraries, such as NVIDIA NeMo Framework, NVIDIA Triton Inference Server, TensorRT, TensorRT-LLM

  • Proficiency in model deployment and optimization techniques for efficient inference on various hardware platforms ·

NVIDIA is widely considered to be one of the world's most desirable employers in the technology field. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

#LI-Hybrid

The base salary range is 184,000 USD - 356,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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Average salary estimate

$270250 / YEARLY (est.)
min
max
$184000K
$356500K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Full Stack Developer, AI and LLM, NVIDIA

NVIDIA's Silicon Solutions Group is on the lookout for a Full Stack Developer specialized in AI and LLM to join our remote team in California, USA! In this exciting role, you'll be at the forefront of integrating cutting-edge AI into our data analysis and automation infrastructure, playing a pivotal role in supporting large-scale automation initiatives. Your day-to-day will involve collaborating with developers and cross-functional teams to tackle current and emerging challenges head-on, all while designing innovative AI solutions to enhance existing workflows. Your hands-on experience will be invaluable as you lead the charge in AI planning, design, and the implementation of generative solutions, particularly in the realm of Large Language Models (LLM). We want someone who thrives in a dynamic environment, eager to study and develop groundbreaking techniques in deep learning and machine learning. Apart from your top-notch skills in Python, C++, and deep learning frameworks, your collaborative spirit and strong communication abilities will help drive our mission of excellence and innovation. If you’re a motivated self-starter with a knack for analyzing complex systems, we want to hear from you! At NVIDIA, you'll be among the most talented individuals in the tech world, and we encourage you to explore new ways to succeed professionally while contributing to our goals.

Frequently Asked Questions (FAQs) for Full Stack Developer, AI and LLM Role at NVIDIA
What are the main responsibilities of a Full Stack Developer at NVIDIA?

As a Full Stack Developer at NVIDIA, you'll be responsible for integrating AI solutions into our data analysis and automation infrastructure. This includes designing and implementing end-to-end generative AI solutions, especially around Large Language Model (LLM) training and deployment strategies. You'll work closely with cross-functional teams to tackle challenges and enhance existing automation workflows.

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What qualifications do I need to apply for the Full Stack Developer position at NVIDIA?

To apply for the Full Stack Developer role at NVIDIA, candidates should ideally have an MS degree or equivalent experience with at least 6 years in software development, including 2 years in AI solutions. Proficiency in Python, C++, and deep learning frameworks is essential, alongside demonstrated experience in full-stack development focusing on improving application performance.

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What makes NVIDIA an ideal place for a Full Stack Developer specializing in AI?

NVIDIA is considered one of the most desirable employers in technology due to its commitment to fostering innovation and diversity. Working here means collaborating with some of the brightest minds in the industry while contributing to groundbreaking projects. The work culture encourages independence and creativity, making it an exciting place to grow your career as a Full Stack Developer in AI.

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Is remote work an option for the Full Stack Developer role at NVIDIA?

Yes, the Full Stack Developer role at NVIDIA is available as a remote position based in California. This flexibility allows you to work from the comfort of your home while still being part of a dynamic and collaborative team focused on integrating AI into our operations.

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What skills can help me stand out for the Full Stack Developer position at NVIDIA?

To stand out as a candidate for the Full Stack Developer position at NVIDIA, having experience in CUDA programming, benchmarking, and performance analysis of AI systems will be highly advantageous. Additionally, expertise in training and fine-tuning LLMs using frameworks like TensorFlow or PyTorch will significantly enhance your profile.

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Common Interview Questions for Full Stack Developer, AI and LLM
Can you explain your experience with full-stack development?

When answering this question, emphasize your relevant years of experience in full-stack development, and highlight specific projects where you've demonstrated your skills in both frontend and backend technologies. Mention specific programming languages and frameworks you’re comfortable with, and how you've used them to successfully complete projects.

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What AI techniques have you implemented in previous projects?

Discuss specific AI techniques you've implemented, such as deep learning implementations or improvements to existing algorithms. Highlight any tools or libraries you used, and explain the impact these techniques had on project outcomes or efficiency.

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How do you approach debugging complex systems?

Share your systematic approach to debugging, which may include analyzing logs, reproducing issues, and using debugging tools. Providing a real-life example where you effectively resolved a complex issue can demonstrate your analytical skills.

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What do you consider when designing end-to-end AI solutions?

Explain the key factors you consider, such as data quality, workflow efficiency, deployment strategies, and user experience. Discuss how these elements tie into the overall success of the AI solution.

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Describe a project where you collaborated with a cross-functional team.

Detail a specific project where cross-collaboration was key to success. Highlight your role, the input from other team members, and how collective efforts led to achieving project goals. Emphasize communication and teamwork.

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How do you ensure the performance of applications you develop?

Discuss the various performance metrics you monitor, such as response time, latency, and resource utilization. Mention any tools and techniques you use for performance testing and optimization, and provide examples from your past experience.

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What is your experience with model deployment and optimization techniques?

Share your background in deploying machine learning models, focusing on techniques you've used for optimization. Discuss specific frameworks (like TensorFlow or PyTorch) and tools (like TensorRT or Triton Inference Server) that you are familiar with, emphasizing their importance in making AI models efficient.

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How do you balance multiple projects?

Explain your project management strategies, such as prioritization methods or task management tools. Sharing an instance where you successfully handled multiple projects while meeting deadlines can bolster your credibility.

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What motivates you to work in AI development?

Articulate your passion for AI and how it drives you in your career. Mention specific aspects of AI development that excite you, such as tackling complex problems, contributing to innovations, or the potential impact on various industries.

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What challenges have you encountered in AI projects, and how did you overcome them?

Discuss a real challenge related to AI development you've faced, how you approached the problem, and the resolution process. Highlight what you learned and how that experience has influenced your work ethic or methodologies.

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NVIDIA is a publicly traded, multinational technology company headquartered in Santa Clara, California. NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, and ignited the era of modern AI.

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CULTURE VALUES
Customer-Centric
Mission Driven
Inclusive & Diverse
Rise from Within
Diversity of Opinions
Work/Life Harmony
Growth & Learning
Transparent & Candid
BENEFITS & PERKS
Medical Insurance
Paid Time-Off
Maternity Leave
Mental Health Resources
Equity
Child Care stipend
Paternity Leave
WFH Reimbursements
Flex-Friendly
Dental Insurance
Vision Insurance
Life insurance
Health Savings Account (HSA)
Flexible Spending Account (FSA)
401K Matching
Military leave
FUNDING
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TEAM SIZE
EMPLOYMENT TYPE
Full-time, remote
DATE POSTED
April 11, 2025

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