CUDA Engineer

• Investigate and optimize LLM inference performance on modern GPUs
• Work with inference and serving frameworks such as vLLM, SGLang, TensorRT-LLM, or similar systems
• Analyze GPU execution, memory access patterns, kernel performance, and inference bottlenecks
• Develop, optimize, debug, or reverse-engineer CUDA kernels and low-level GPU operations
• Explore optimization techniques for matrix multiplication, attention mechanisms, and neural network layers
• Benchmark performance and identify opportunities to improve latency, throughput, and GPU utilization
• Work on technically challenging AI systems and high-performance computing problems
• Perform hands-on experimentation and communicate technical findings

• Strong hands-on experience with CUDA and GPU programming
• Deep understanding of GPU architecture, memory hierarchy, parallel execution, and performance optimization
• Experience with LLM inference, AI systems, GPU kernels, or high-performance computing
• Familiarity with vLLM, SGLang, TensorRT-LLM, Triton, or FlashAttention
• Experience debugging complex performance issues and investigating low-level system behavior
• Strong problem-solving skills
• Ability to communicate complex technical concepts in English
• PhD or research experience in Computer Science, Machine Learning, Computer Architecture, or a related field (nice to have)
• Publications, research projects, or meaningful contributions to open-source GPU/LLM infrastructure (nice to have)
• Experience with PyTorch internals, distributed inference, quantization, KV cache optimization, or custom GPU kernels (nice to have)
• Contributions to vLLM, SGLang, Triton, FlashAttention, or related repositories (nice to have)

• Security through careful client vetting and reliable, timely payments
• Career support and assistance finding new project opportunities
• Legal guidance for independent contractor or sole proprietorship status, taxes, and related processes
• English courses
• Professional growth opportunities
• Team-building events
• People-first management with minimal bureaucracy
• Friendly company culture
• Flexible working hours
• 29 days of PTO (18 working days per year plus all national holidays)
• 10 paid recovery days
• Full financial and legal support for independent contractors
• Free English classes with native speakers or Ukrainian teachers
• Dedicated HR support