CUDA Engineer

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.

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.

Your day-to-day in this position

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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 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

Our next steps

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Requirements

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