CUDA to Python Code Translation Expert

About OpenTrain

OpenTrain is the leading platform for finding and building careers in AI training and data labeling. OpenTrain AI is recruiting contractors for specialized work that helps improve the systems behind modern artificial intelligence.

Create a free OpenTrain account to build your AI training profile and apply to opportunities in minutes. This role is available to candidates in India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Brazil, and Mexico.

About AI Training and RLHF

AI training is the human work behind today’s models. Technical contributors review code, evaluate model-generated answers, write examples, and provide structured feedback so AI systems become more accurate, useful, and reliable.

In reinforcement learning from human feedback, or RLHF, experts compare model responses and explain their decisions. Your CUDA and Python knowledge will help identify whether generated code preserves logic, numerical behavior, and GPU-oriented intent.

The Role

OpenTrain is seeking a CUDA to Python Code Translation Expert for a project supporting leading LLM companies. You will translate CUDA and C++ code into Python implementations with PyTorch and NumPy, assess LLM-generated translations, and contribute to RLHF workflows.

This is a part-time contractor opportunity requiring 20 or more hours per week. The listed experience level is entry level, while the role requirements call for at least five years of overall work experience, including three or more years with Python and two or more years with CUDA or C++.

• Employment type: Contractor and part time
• Time commitment: 20+ hours per week
• Working language: Fluent written and conversational English
• Eligible countries: India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Brazil, and Mexico

What You’ll Do

You will work across code translation, technical evaluation, debugging, prompt development, and documentation. The work calls for careful analysis of GPU-accelerated logic and clear explanations of technical judgments.

• Translate CUDA and C++ kernels into equivalent Python implementations using PyTorch and NumPy.
• Preserve logical and performance parity when porting GPU code across languages.
• Analyze CUDA kernels and GPU-accelerated code for structure and efficiency before translation.
• Evaluate LLM-generated Python translations for correctness and numerical consistency.
• Debug translated Python code for correctness, readability, and consistency with industry standards.
• Develop test prompts with prompt engineers and researchers for real-world CUDA and PyTorch tasks.
• Rank LLM responses in RLHF workflows and clearly justify each ranking decision.
• Maintain technical documentation that supports reproducibility and code clarity.
• Identify common LLM failure patterns and propose improvements to prompts or conversion approaches.

Required Qualifications

This role requires substantial programming experience and the ability to reason about parallel GPU computation, numerical behavior, and cross-language implementation details.

• At least five years of overall work experience.
• At least three years of experience with Python.
• At least two years of experience with CUDA or C++.
• Strong hands-on experience with PyTorch, NumPy, and scientific computing.
• Solid understanding of CUDA programming concepts and C++ fundamentals.
• Ability to analyze CUDA kernels and accurately reproduce them in Python.
• Knowledge of GPU computation, parallelism, and performance-aware coding practices.
• Strong debugging skills and close attention to numerical consistency.
• Strong written and conversational English communication skills.
• Knowledge of CUDA thread hierarchy and memory management.

Helpful Background

Experience evaluating AI-generated code or participating in LLM tuning is a plus. Familiarity with RLHF, code evaluation, or technical feedback workflows can help you contribute effectively, although the core requirements are centered on CUDA, C++, Python, PyTorch, and NumPy.

Why Work in AI Training

AI training combines technical expertise with a direct role in shaping cutting-edge systems. Contributors help models understand and generate better code, while often gaining flexible project-based work that can fit around other commitments.

OpenTrain brings together opportunities for people building careers in data labeling and AI training. Apply through your free OpenTrain account and use your technical background to contribute to how advanced AI systems are built.

• Contribute directly to modern AI development.
• Use specialized programming expertise in model evaluation and improvement.
• Work on flexible, part-time AI training projects.
• Build experience in code evaluation, RLHF, and technical data work.