About The Position
NVIDIA is hiring a new college graduate to build performance models that help the company understand how evolving LLM architectures and inference workloads map to hardware. The team combines simulation and agentic engineering to evaluate emerging architectures and inform hardware and software decisions. The role involves building and validating performance models for LLM architectures across GPU, LPU, and heterogeneous systems; developing agents to automate simulation workflows, analyze bottlenecks, and accelerate design space exploration; and collaborating with hardware architecture, inference, runtime, and compiler teams to improve modeling accuracy and guide optimization.
Requirements
- Recently completed a master's degree in Computer Science or a related field, or equivalent experience.
- Familiarity with modern LLM architectures and their inference characteristics.
- Experience with simulation, profiling, or performance modeling, including roofline analysis for LLM inference.
- Strong analytical skills and a rigorous approach to experimentation and validation.
- Experience building reliable engineering tools using coding agents.
Nice To Haves
- Experience building agents that automate complex engineering workflows.
- Knowledge of accelerator architecture and compute, memory, or communication bottlenecks.
- Open-source contributions in agentic systems, simulation, or inference optimization.
Responsibilities
- Build and validate performance models for LLM architectures across GPU, LPU, and heterogeneous systems.
- Develop agents to automate simulation workflows, analyze bottlenecks, and accelerate design space exploration.
- Collaborate with hardware architecture, inference, runtime, and compiler teams to improve modeling accuracy and guide optimization.
Benefits
- Equity
- Benefits (not further specified)
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
