Senior Applied LLM Engineer, AI – Chip Design at NVIDIA

Santa Clara, California, United States

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$148,000 – $287,500Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, SemiconductorsIndustries

Requirements

Master’s or PhD degree in Electrical Engineering, Computer Science/Engineering, or a related discipline (or equivalent experience)
5+ years of proven industry experience
Proficiency in rapid prototyping using languages like Python and C++, with strong foundational knowledge of data structures, algorithms, and software engineering principles
Familiarity with training and fine-tuning large language models, advanced Retrieval-Augmented Generation (RAG) pipelines, vector databases and agentic frameworks
Strong analytical, communication, and interpersonal skills, with a proven ability to thrive in dynamic, product-focused, and distributed teams
A proactive approach to problem-solving and a willingness to acquire new skills and knowledge

Responsibilities

Develop and optimize retrieval and generation algorithms for enterprise data (text, code, and images) to build advanced AI applications
Drive impact by designing and deploying LLM-powered solutions for engineering assistants and multi-turn, multi-modal dialogue systems
Leverage AI technologies to solve complex problems in chip design, driving innovation and meaningful impact
Engage with the latest advancements in machine learning and AI to create state-of-the-art solutions
Lead with purpose and maintain high-quality engineering practices

Skills

Key technologies and capabilities for this role

PythonC++Data StructuresAlgorithmsLLM TrainingLLM Fine-TuningRAGVector DatabasesAgentic FrameworksMachine Learning

Questions & Answers

Common questions about this position

What is the salary range for this Senior Applied LLM Engineer position?

The base salary range is $148,000 - $287,500 USD.

Is this role remote or hybrid, and where is it located?

The position is hybrid.

What skills and experience are required for this role?

Candidates need a Master’s or PhD in Electrical Engineering, Computer Science/Engineering, or related field, 5+ years of industry experience, proficiency in Python and C++ for rapid prototyping, and familiarity with training/fine-tuning LLMs, advanced RAG pipelines, vector databases, and agentic frameworks. Strong analytical, communication, and interpersonal skills are also required.

What is the company culture like at NVIDIA for this team?

The role involves thriving in dynamic, product-focused, and distributed teams, with a proactive approach to problem-solving in a fast-paced environment at the forefront of AI innovation.

What makes a strong candidate for this Senior Applied LLM Engineer role?

A strong candidate has a Master’s or PhD, 5+ years of industry experience, proficiency in Python/C++ and LLM technologies like fine-tuning and RAG, plus strong soft skills to excel in dynamic, distributed teams.

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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