CUDA Engineer

Description

MWDN is a global IT outstaffing company with 23+ years of experience that connects exceptional tech talent with leading companies across Israel, the USA, Great Britain, and Western Europe. We offer opportunities to work on international products in a stable and professional environment.

Why does MWDN rock?

Here’s what you can expect when you join MWDN:

• Security: We carefully vet our clients to minimize risks and ensure reliability and timely payments - no fraud or unpleasant surprises.
• Career support: If a project isn’t the right fit, we support you and actively help find new opportunities that match your skills and career goals.
• Legal assistance: We provide guidance on legal matters, including opening and managing your independent contractor or sole proprietorship status, taxes, and related processes.
• Professional development: We offer English courses and professional growth opportunities, as well as team-building events.

Why choose us? MWDN is ranked among the top 5 IT employers in our region according to DOU. We take pride in our transparency and strong commitment to our team. Curious to learn more? See what our employees say about working with us on DOU.

What is your new project?

We’re looking for a highly technical engineer or researcher with deep expertise in GPU computing, CUDA, and LLM inference optimization to work on challenging problems at the intersection of AI systems and high-performance computing.

This opportunity is ideal for someone who enjoys understanding how things work under the hood - from GPU architecture and low-level kernels to LLM inference engines and performance bottlenecks.

What makes this project exciting?

• 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 problems requiring strong analytical thinking and hands-on experimentation.

What makes you a great fit

• 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 one or more frameworks such as vLLM, SGLang, TensorRT-LLM, Triton, or FlashAttention.
• Experience debugging complex performance issues and investigating low-level system behavior.
• Strong problem-solving skills and the ability to communicate complex technical concepts in English.

Nice to have

• PhD or research experience in Computer Science, Machine Learning, Computer Architecture, or a related field.
• Publications, research projects, or meaningful contributions to open-source GPU/LLM infrastructure.
• Experience with PyTorch internals, distributed inference, quantization, KV cache optimization, or custom GPU kernels.
• Contributions to projects such as vLLM, SGLang, Triton, FlashAttention, or related repositories.

Why work with us?

• People-first management with minimal bureaucracy
• A friendly company culture, proven by employees who choose to return
• Flexible working hours
• 29 days of PTO (18 working days per year pluse 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