Full-Time

Senior Applied LLM Engineer

AI, Chip Design

Confirmed live in the last 24 hours

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI computing solutions

Automotive & Transportation
Enterprise Software
AI & Machine Learning
Gaming

Compensation Overview

$148k - $276kAnnually

+ Equity

Senior

Santa Clara, CA, USA

Category
Applied Machine Learning
AI Research
AI & Machine Learning
Electrical Engineering
Hardware Engineering
Required Skills
Python
Data Structures & Algorithms
C/C++
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 as needed to achieve results.
Responsibilities
  • Develop and optimize retrieval and generation algorithms for enterprise data (text, code, and images) to build advanced AI applications that transform chip design.
  • Drive impact by designing and deploying LLM-powered solutions for engineering assistants and multi-turn, multi-modal dialogue systems.
  • Make a difference by leveraging AI technologies to solve complex problems in chip design, driving innovation and meaningful impact across the industry.
  • Join a dynamic, collaborative team where creativity and fresh ideas are encouraged.
  • Stay ahead by engaging 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 that inspire others to achieve excellence.

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.

Company Stage

IPO

Total Funding

$19.5M

Headquarters

Santa Clara, California

Founded

1993

Growth & Insights
Headcount

6 month growth

9%

1 year growth

27%

2 year growth

45%
Simplify Jobs

Simplify's Take

What believers are saying

  • NVIDIA's investment in Ayar Labs boosts scalable AI infrastructure with optical interconnect solutions.
  • Acquiring VinBrain enhances NVIDIA's AI capabilities in healthcare and smart city applications.
  • Participation in Nebius Group's funding expands NVIDIA's AI infrastructure across continents.

What critics are saying

  • Increased competition from Ayar Labs challenges NVIDIA's AI hardware market position.
  • VinBrain acquisition may face integration challenges, affecting operational efficiency.
  • Investment in Nebius Group could lead to internal competition for resources and market share.

What makes NVIDIA unique

  • NVIDIA leads in AI and HPC with cutting-edge GPU and SoC technologies.
  • The company excels in diverse markets: gaming, data centers, and autonomous vehicles.
  • NVIDIA's cloud services, like CloudXR, enhance scalable AI and machine learning applications.

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