Cuda/C++ and Python Developer

What does day-to-day look like:

• Translate CUDA/C++ code into equivalent Python implementations using PyTorch and NumPy, ensuring logical and performance parity.
• Analyze CUDA kernels and GPU-accelerated code for structure, efficiency, and function before translation.
• Evaluate LLM-generated translations of CUDA/C++ code to Python, providing technical feedback and corrections.
• Collaborate with prompt engineers and researchers to develop test prompts that reflect real-world CUDA/PyTorch tasks.
• Participate in RLHF workflows, ranking LLM responses and justifying ranking decisions clearly.
• Debug and review translated Python code for correctness, readability, and consistency with industry standards.
• Maintain technical documentation to support reproducibility and code clarity.
• Propose enhancements to prompt structure or conversion approaches based on common LLM failure patterns.

Requirements:

• 5+ years of overall work experience, with at least 3 years of relevant experience in Python and 2+ years in CUDA/C++.
• Strong hands-on experience with Python, especially in scientific computing using PyTorch and NumPy.
• Solid understanding of CUDA programming concepts and C++ fundamentals.
• Demonstrated ability to analyze CUDA kernels and accurately reproduce them in Python.
• Familiarity with GPU computation, parallelism, and performance-aware coding practices.
• Strong debugging skills and attention to numerical consistency when porting logic across languages.
• Experience evaluating AI-generated code or participating in LLM tuning is a plus.
• Ability to communicate technical feedback clearly and constructively.
• Fluent in conversational and written English communication skills.