AI Performance Engineer - New Grad

SambaNova Systems · Austin, Texas, United States; San Jose, California, United States · Engineering

Posted 2026-10-21

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About the Team

The AI Performance team brings up and optimizes foundation models such as DeepSeek, Llama, Qwen, and GPT OSS on SambaNova's dataflow platform. We profile and tune models across the compiler, runtime, and hardware layers to improve inference throughput and latency.

About the Role

As a new grad AI Performance Engineer, you'll bring up new open source models on the SambaNova stack and work to make them run faster. You'll profile model execution, find bottlenecks, and apply optimizations such as quantization, kernel fusion, and improved scheduling with the compiler, runtime, and hardware teams.

Responsibilities

Bring up new foundation models on the SambaNova platform using our software stack

Profile model performance across the compiler, runtime, and hardware layers

Identify bottlenecks and propose dataflow or scheduling optimizations for single-node and distributed systems

Apply techniques from recent research in quantization, scheduling, and memory optimization

Benchmark throughput and latency and track performance changes across releases

Work with the machine learning, compiler, runtime, and hardware teams to ship performance improvements into SambaNova products

Required Qualifications

B.S. in Computer Science, Electrical Engineering, or related field

Strong programming skills in Python or C++

Understanding of algorithms, data structures, and numerical computing

Experience with PyTorch, TensorFlow, or JAX

Experience with inference frameworks such as vLLM, TensorRT, or SGLang

GPU programming experience with CUDA or Triton

Preferred Qualifications

M.S. or Ph.D. in Computer Science, Electrical Engineering, or related field

Experience with LLM training or inference

Familiarity with quantization, graph optimization, kernel fusion, or model partitioning

Knowledge of memory hierarchy, caching, and scheduling for large model execution

Internship or research experience in ML systems or performance optimization

Publications or open source contributions in ML systems

Base Salary Range:

Base Pay Range

$131,200—$196,800 USD

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