Overview
Remote
On Site
USD 180,000.00 per year
Full Time
Skills
Large Language Models (LLMs)
Algorithms
Research and Development
Research
Generative Artificial Intelligence (AI)
Workload Analysis
Optimization
Workflow
Use cases
Collaboration
Communication
Computer hardware
Computer science
Electrical engineering
Computer engineering
Deep learning
Systems design
Python
C++
Computer architecture
LangChain
LlamaIndex
Modeling
CUDA
OpenCL
Computer graphics
Artificial intelligence
GPU
Robotics
Innovation
Recruiting
Promotions
SAP BASIS
Law
Job Details
At NVIDIA, we are at the forefront of the constantly evolving field of large language models, and their application in agentic use cases. As the scale and complexity of these agentic systems continues to increase, we are seeking outstanding engineers to join our team and help shape the future agentic inference.
Our team is dedicated to pushing the boundaries of what's possible with agentic LLMs by improving the algorithmic performance and efficiency of systems that represent them. We constantly reflect on how to improve these systems, developing new inference algorithms and protocols, improving existing models, and seamlessly integrating improvements to ensure NVIDIA's solutions can efficiently handle large-scale, sophisticated tasks.
What you'll be doing:
What we need to see:
Ways to stand out from the crowd:
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology-and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.
The base salary range is 180,000 USD - 339,250 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.
Our team is dedicated to pushing the boundaries of what's possible with agentic LLMs by improving the algorithmic performance and efficiency of systems that represent them. We constantly reflect on how to improve these systems, developing new inference algorithms and protocols, improving existing models, and seamlessly integrating improvements to ensure NVIDIA's solutions can efficiently handle large-scale, sophisticated tasks.
What you'll be doing:
- Research and Development: Explore and incorporate contemporary research on generative AI, agents, and inference systems into the NVIDIA LLM software stack.
- Workload Analysis and Optimization: Conduct in-depth analysis, profiling, and optimization of agentic LLM workloads to significantly reduce request latency and increase request throughput while maintaining workflow fidelity.
- System Design and Implementation: Design and implement scalable systems to accelerate agentic workflows and efficiently handle sophisticated datacenter-scale use cases.
- Collaboration and Communication: Advise future iterations of NVIDIA software, hardware, and system by engaging with a diverse set of teams at NVIDIA and external partners and formalizing the strategic requirements presented by their workloads.
What we need to see:
- BS, MS, PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent experience).
- 3+ years of experience in deep learning and deep learning systems design.
- Proficiency in Python and C++ programming
- Strong understanding of computer architecture, and GPU/parallel datacenter computing
- fundamentals.
- Proven interest in analyzing, modeling, and tuning application performance.
Ways to stand out from the crowd:
- 2+ years of experience in building large-scale LLM inference systems, especially those involving compound AI.
- Experience with agentic LLM frameworks such as Langchain and LLamaIndex.
- Experience with processor and system-level performance modeling.
- GPU programming experience with CUDA or OpenCL.
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology-and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.
The base salary range is 180,000 USD - 339,250 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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.