GPU Programmer - Remote

YO AI Labs View all jobs
Seattle, WA, United States
14 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$43,680.0 - $52,000.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence C++ (Programming Language) Computer Aided Three-Dimensional Interactive Application (CATIA) Nvidia CUDA OpenGL Shading Language Performance Tuning Scientific Computating Graphics Processing Unit (GPU) Large Language Models Gpu Programming Enovia

Job description

Design, implement, and optimize GPU software using CUDA, WebGPU, or GLSL. Profile and optimize GPU kernels and shaders for performance and efficiency. Develop host-side logic and GPU integrations using C++. Create GPU-focused tasks and solutions for AI/LLM applications. Analyze performance bottlenecks and implement optimization strategies., Role: CAA Programmer - CATIA / Enovia CAA Location: Remote (USA) Employment Type: Full-Time Visa Type: USC / GC Only Must-Have Qualifications: 5+ years of experience in C…

Requirements

We are seeking experienced GPU Programmers / Software Engineers to design and optimize GPU-based tasks for AI and LLM applications. You will apply your expertise in GPU programming, performance optimization, and C++ development to build high-performance solutions., Strong experience with GPU programming, particularly on NVIDIA GPUs. Proficiency in CUDA, WebGPU, or GLSL. Strong C++ programming skills. Background in graphics programming, ML acceleration, scientific computing, HPC, or related GPU-focused fields. Strong understanding of GPU architecture and performan

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:30 min

Exploring the Python-enabled GPU programming software stack

Paul Graham Paul Graham Ā· World Congress 2026 Europe

48 sec

Transitioning from scaling GPU workloads to building coding agents

Alex Laubscher Alex Laubscher Ā· World Congress 2025

6:21 min

Previewing upcoming hardware acceleration capabilities for Python environments

Chris Heilmann +2 Ā· LIVE

3:32 min

Evolution of general purpose GPU computing and Python

Paul Graham Paul Graham Ā· World Congress 2025

1:37 min

Accelerating compute with focused developer tools

Julia Koch Julia Koch +1 Ā· World Congress 2026 Europe

3:30 min

Transitioning from CUDA software architect to user

Stephen Jones Ā· Coffee With Developers

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