GPU Engineer

KOG

. Develop and optimize GPU kernels using C++, CUDA, HIP, and low-level instructions .

Posted 11/9/2026full-timeRemote • FranceMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and optimizing GPU kernels using C++, CUDA, and HIP, with a strong focus on performance profiling and benchmarking. Proven ability to take ownership of technical projects and implement AI models on NVIDIA and AMD GPUs.

Highest-signal resume keywords

GPU Kernel DevelopmentCUDA C++ OptimizationPerformance ProfilingAI Model ImplementationTechnical Project Ownership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

C++CUDAHIPGPU ArchitectureMemory AccessSynchronizationExecution BottlenecksProfilingBenchmarkingInference Optimization

Tools & Technologies

NVIDIA GPUsAMD GPUsPTXCDNA ISAMulti-GPU Systems

Industry Keywords

HPCAI AgentsLow-Latency InferenceGPU Performance Portability

Tech Stack

Tools & technologies

C++

About the role

Key responsibilities & impact

Develop and optimize GPU kernels using C++, CUDA, HIP, and low-level instructions
Investigate GPU architecture, memory access, synchronization, and execution bottlenecks
Profile and benchmark workloads to identify and validate performance improvements
Optimize inference operations and communication across multiple GPUs
Implement and optimize new AI models on NVIDIA and AMD GPUs
Help build AI agents for GPU engineering, enabling automated code optimization, correctness testing, benchmarking, and iterative improvements
Take ownership of technical decisions and their implementation

Requirements

What you’ll need

Strong hands-on experience developing and optimizing GPU kernels, ideally using CUDA C++ or HIP/ROCm
Deep understanding of GPU architecture, memory hierarchy, parallel execution, and performance bottlenecks
Strong C++ skills and experience profiling and benchmarking GPU workloads
Proven ownership of challenging technical projects, from implementation to measured results
Interest in developing AI agents and tools to accelerate GPU engineering
Experience with PTX, CDNA ISA, multi-GPU systems, low-latency inference, or GPU performance portability is particularly valuable
A PhD in HPC, computer science, or a related field is a plus when backed by substantial engineering work
Candidates must already be based in Paris or elsewhere in Île-de-France
Availability to join the team quickly