Senior LLM Inference & Algorithms Engineer Remote, Equity

NVIDIA; United States; On-site; USD 272,000 - 431,250; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is advancing the frontier of large language models and their practical deployment. We seek outstanding engineers to join our team to push the performance and efficiency of LLM inference across datacenter-scale workloads.

You will work on scalable systems, run workloads to optimize latency and throughput, and collaborate across multiple teams to define requirements for state-of-the-art AI solutions.

Qualifications

• BS, MS, or PhD in Computer Science, Electrical Engineering, Computer Engineering, or related field (or equivalent experience).
• 15+ 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.

Responsibilities

• 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: Profile and optimize agentic LLM workloads to reduce latency and increase throughput while maintaining fidelity.
• System Design and Implementation: Design scalable systems to accelerate agentic workflows and handle datacenter-scale use cases.
• Collaboration and Communication: Advise iterations of NVIDIA software, hardware, and systems by engaging with teams at NVIDIA and external partners and formalizing requirements.

Skills

Python

C++

Deep learning systems

GPU/parallel computing

Performance modeling

Education

BS/MS/PhD in Computer Science / Electrical Engineering / Computer Engineering

Tools

CUDA

OpenCL

Job description

NVIDIA is advancing the frontier of large language models and their practical deployment. We seek outstanding engineers to join our team to push the performance and efficiency of LLM inference across datacenter-scale workloads.

You will work on scalable systems, run workloads to optimize latency and throughput, and collaborate across multiple teams to define requirements for state-of-the-art AI solutions.