AI Performance Engineer - New Grad

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AI Performance Engineer - New Grad in USA

SambaNova Systems
Full time
Email

USA
10/21/2026
Report

Austin, TX

Responsibilities

Bring up new foundation models on the SambaNova platform using its software stack.
Profile model performance across compiler, runtime, and hardware layers.
Identify bottlenecks and propose dataflow or scheduling optimizations for single-node and distributed systems.
Apply quantization, scheduling, and memory optimization techniques.
Benchmark inference throughput and latency and track performance across releases.
Collaborate with machine learning, compiler, runtime, and hardware teams to ship performance improvements.

Requirements

Bachelor’s degree in Computer Science, Electrical Engineering, or a 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: master’s or Ph.D. in a relevant field, LLM training or inference experience, familiarity with quantization, graph optimization, kernel fusion, or model partitioning, and knowledge of memory hierarchy, caching, and scheduling.
Preferred: internship or research experience in ML systems or performance optimization, plus publications or open-source contributions in ML systems.

Benefits

US-based full-time employees receive medical, dental, vision, disability, life, AD&D, and flexible spending account benefits.
The company covers 95% of employee medical insurance premiums and 77% of dependent premiums, with an employer HSA contribution.
Benefits include equity, Headspace, Gympass+, One Medical, counseling services, and an Employee Assistance Program.

Salary: $131k - $197k/yr

SambaNova Systems

Welcome to SambaNova: Revolutionizing AI Capacity At SambaNova, we're empowering developers, enterprises, governments, and data centers to unlock their full AI potential. Our full-stack infrastructure, from chips to models, enables lightning-fast performance, low power consumption, and high-effic...

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