GPU Kernel Engineer – CUDA, Triton, Accelerator Performance

Anyone AI

. Review GPU and accelerator kernel implementations for correctness .

Posted 9/15/2026contractRemote • ArgentinaMid-LevelSenior💰 $65 per hourWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing, optimizing, and debugging GPU and accelerator kernels, with a strong focus on performance optimization and numerical correctness. Proficient in using profiling tools and translating kernels across frameworks while identifying and resolving technical challenges.

Highest-signal resume keywords

CUDATritonGPU Performance OptimizationKernel Profiling ToolsFloating-Point Numerical Correctness

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

GPU Kernel DevelopmentKernel OptimizationDebugging Kernel IssuesKernel ProfilingMemory Hierarchy OptimizationPerformance BenchmarkingKernel TranslationOperator FusionPerformance Bottleneck IdentificationNumerical Tolerance Evaluation

Soft Skills

Clear Technical FeedbackProblem-Solving

Tools & Technologies

NsightNCURoofline AnalysisCuBLASCuDNNAWS NeuronTPUJAXMLIRXLA

Industry Keywords

GPU EcosystemAccelerator EcosystemAI Workload PerformanceKernel LibrariesTechnical Benchmark Development

Tech Stack

Tools & technologies

AWS

About the role

Key responsibilities & impact

Review GPU and accelerator kernel implementations for correctness
Compare outputs against reference implementations
Evaluate numerical tolerance thresholds
Review kernel benchmarks and determine whether comparisons are fair
Identify performance bottlenecks and optimization opportunities
Assess whether performance targets are realistic given hardware limits
Review kernel translations and hardware migrations
Identify compilation, driver, memory, shape, and runtime issues
Determine whether technical tasks are genuinely difficult or incorrectly configured
Provide clear, actionable technical feedback
Implement and debug kernels
Optimize CUDA and Triton kernels
Translate between kernel frameworks
Perform hardware migration and operator fusion
Profile and benchmark performance
Verify numerical correctness
Debug compilation and runtime issues
Optimize memory hierarchy and kernel-level AI workload performance

Requirements

What you’ll need

3+ years of hands-on experience developing, optimizing, or debugging GPU or accelerator kernels
Strong experience with at least two of: 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, and 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
Experience writing kernels from technical specifications, translating kernels between frameworks, migrating kernels across hardware platforms, debugging incorrect implementations, optimizing kernel performance, and fusing multiple operations into optimized kernels
Experience across both NVIDIA GPU and custom accelerator ecosystems (nice to have)
Experience with AWS Trainium, TPU, JAX, or other accelerators (nice to have)
Compiler engineering experience (nice to have)
Familiarity with MLIR, XLA, or intermediate representation lowering (nice to have)
Contributions to GPU or ML kernel libraries (nice to have)
Experience with cuBLAS, cuDNN, Triton community kernels, or JAX/XLA custom calls (nice to have)
Experience with AI model evaluation, RLHF, or technical benchmark development (nice to have)

Benefits

Comp & perks

$65 per hour compensation
Part-time, project-based consulting engagement
Remote work