# GPU Kernel Engineer – CUDA, Triton & Accelerator Performance at Anyone AI

> Open job at Anyone AI in Madrid, Spain. Workplace: Remote (Spain).

Source: Spain Dev Jobs, https://spain-devjobs.com/jobs/anyone-ai-gpu-kernel-engineer-cuda-triton-accelerator-performance-e7px63v
Posted 15 September 2026. Last checked on the employer's career site: 10 November 2026.

## Facts

- Company: [Anyone AI](https://spain-devjobs.com/companies/anyone-ai)
- Location: Madrid, Spain
- Workplace: Remote (Spain)
- Employment type: Contract
- Spanish: Not required
- Skills: AWS
- Not mentioned in the job post: salary, visa sponsorship, relocation, where you can apply from

## Job description

Anyone AI is recruiting experienced **GPU Kernel Engineers** for a specialized project focused on reviewing, debugging, and evaluating high-performance compute kernels used in AI workloads.

We’re looking for engineers with hands-on experience writing and optimizing kernels across frameworks such as **CUDA, Triton, NKI, or Pallas**, with a strong understanding of numerical correctness, GPU performance, memory optimization, and benchmarking.

### What You’ll Work On

You’ll work with GPU and accelerator kernel tasks involving:

- Kernel implementation and debugging
- CUDA and Triton optimization
- Translation between kernel frameworks
- Hardware migration
- Operator fusion
- Performance profiling and benchmarking
- Numerical correctness verification
- Compilation and runtime debugging
- Memory hierarchy optimization
- Kernel-level AI workload performance

You’ll assess whether implementations are technically correct, efficiently designed, reproducible, and appropriately optimized for the target hardware.

### What We’re Looking For

- **3+ years of hands-on experience** developing, optimizing, or debugging GPU or accelerator kernels
- Strong experience with at least **two** of the following:
  - CUDA
  - Triton
  - NKI / AWS Neuron
  - Pallas / JAX
- Strong understanding of GPU performance optimization
- Experience with kernel profiling tools such as **Nsight, NCU, roofline analysis, or framework-native profilers**
- Understanding of:
  - Memory bandwidth
  - Compute throughput
  - GPU occupancy
  - Shared memory
  - Register pressure
  - Memory coalescing
  - Bank conflicts
- Strong understanding of floating-point numerical correctness and tolerance thresholds
- Experience debugging kernel compilation and runtime issues
- Ability to distinguish software defects, environment problems, and genuine optimization challenges

### Relevant Experience

Candidates should have experience with several of the following types of work:

- Writing kernels from technical specifications
- Translating kernels between CUDA, Triton, or other frameworks
- Migrating kernels across hardware platforms
- Debugging incorrect kernel implementations
- Optimizing kernel performance
- Fusing multiple operations into optimized kernels

### Nice to Have

- Experience across both **NVIDIA GPU and custom accelerator ecosystems**
- Experience with AWS Trainium, TPU, JAX, or other accelerators
- Compiler engineering experience
- Familiarity with MLIR, XLA, or intermediate representation lowering
- Contributions to GPU or ML kernel libraries
- Experience with cuBLAS, cuDNN, Triton community kernels, or JAX/XLA custom calls
- Experience with AI model evaluation, RLHF, or technical benchmark development

### What You’ll Be Responsible For

- Reviewing GPU and accelerator kernel implementations for correctness
- Comparing outputs against reference implementations
- Evaluating numerical tolerance thresholds
- Reviewing kernel benchmarks and determining whether comparisons are fair
- Identifying performance bottlenecks and optimization opportunities
- Assessing whether performance targets are realistic given hardware limits
- Reviewing kernel translations and hardware migrations
- Identifying compilation, driver, memory, shape, and runtime issues
- Determining whether technical tasks are genuinely difficult or incorrectly configured
- Providing clear, actionable technical feedback

### Engagement

**Work Type:** Remote
**Engagement:** Part-time, project-based consulting
**Focus:** GPU kernels, performance engineering, debugging, and technical evaluation

This role is ideal for engineers who enjoy working close to the hardware, **optimizing GPU workloads, debugging low-level performance issues, and pushing AI compute systems toward their performance limits.**

## How to apply

Apply on the job page, https://spain-devjobs.com/jobs/anyone-ai-gpu-kernel-engineer-cuda-triton-accelerator-performance-e7px63v: its Apply button opens the employer's own application page.

## More jobs from Anyone AI

- [AI Coding Evaluator](https://spain-devjobs.com/jobs/anyone-ai-ai-coding-evaluator-h1wcy7m): Anyone AI, Madrid, Spain. Remote (Spain). Posted 12 October 2026.
- [AI Agent Evaluator](https://spain-devjobs.com/jobs/anyone-ai-ai-agent-evaluator-8fy2v3j): Anyone AI, Madrid, Spain. Remote (Spain). Posted 12 October 2026.
- [Senior Software Engineer – Open Source & SWE-Bench Evaluation](https://spain-devjobs.com/jobs/anyone-ai-senior-software-engineer-open-source-swe-bench-evaluation-03cccub): Anyone AI, Madrid, Spain. Remote (Spain). Posted 10 October 2026.
- [Application Security Engineer – CVE & Vulnerability Research](https://spain-devjobs.com/jobs/anyone-ai-application-security-engineer-cve-vulnerability-research-ztjwm9q): Anyone AI, Madrid, Spain. Remote (Spain). Posted 10 October 2026.
- [Machine Learning Engineer – ML Evaluation & Experiment Design](https://spain-devjobs.com/jobs/anyone-ai-machine-learning-engineer-ml-evaluation-experiment-design-ayz5ecl): Anyone AI, Madrid, Spain. Remote (Spain). Posted 15 September 2026.