CUDA and PyTorch Code Evaluation Expert

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this role and the #1 platform for finding and building careers in AI training and data labeling. It helps skilled contributors discover specialized projects, build a credible AI training profile, and grow their experience in a fast-moving technology field.

• Contractor opportunity with part-time employment classification
• Work commitment of 20+ hours per week
• Applications accepted from India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Brazil, and Mexico

About AI Training and Code Evaluation

AI training is the human side of building modern artificial intelligence. Contributors prepare examples, review model outputs, write prompts, and provide detailed feedback that helps language models produce more accurate and useful results.

In this role, your programming expertise will help evaluate coding data and reinforcement-learning feedback workflows. Rather than building or fine-tuning language models, you will assess whether AI-generated code accurately reflects complex CUDA and C++ programs.

• Help improve language models through coding data and human feedback
• Work with programming prompts, model responses, and evaluation criteria
• Contribute to cutting-edge AI development using your GPU programming knowledge

The Role

OpenTrain is seeking a CUDA and PyTorch Code Evaluation Expert to translate CUDA and C++ code into equivalent Python implementations using PyTorch and NumPy. You will determine whether translated code preserves the original algorithm, numerical behavior, readability, and performance characteristics.

The work combines hands-on GPU programming knowledge with careful review of AI-generated code. You will analyze CUDA kernels, debug translations, create practical coding tasks, and explain technical judgments clearly.

• Translate CUDA and C++ code into Python with PyTorch and NumPy
• Evaluate whether translated code preserves logical and numerical behavior
• Review model-generated code instead of building or fine-tuning language models

What You'll Do

You will work across code translation, testing, evaluation, and technical documentation. Your feedback should be precise, constructive, and detailed enough to support reliable model improvement and reproducible coding examples.

• Analyze CUDA kernels and GPU-accelerated code before reproducing their behavior in Python
• Preserve logical behavior, numerical consistency, readability, and performance characteristics during translation
• Review language-model-generated code translations and identify errors
• Recommend precise corrections for incorrect or incomplete implementations
• Create prompts and test cases based on practical CUDA and PyTorch programming tasks
• Rank language-model responses in reinforcement-learning feedback workflows
• Explain the reasoning behind each response ranking clearly
• Debug translated Python code
• Maintain technical documentation supporting reproducibility and code clarity
• Recommend improvements to prompt structures and code-conversion methods based on recurring model failures

Required Skills and Experience

The listing identifies this opportunity as entry level, while the role requirements call for substantial professional experience. You should have at least five years of overall professional experience, including three or more years working with Python and two or more years working with CUDA and C++.

• Strong hands-on Python experience in scientific computing
• Practical experience with PyTorch and NumPy
• Solid understanding of CUDA programming concepts and kernel analysis
• C++ fundamentals and experience with GPU computation and parallelism
• Performance-aware programming skills
• Ability to reproduce CUDA kernel behavior accurately in Python
• Strong debugging skills and attention to numerical consistency
• Ability to evaluate AI-generated code and justify technical rankings
• Clear, constructive technical communication
• Fluent written and conversational English

Helpful Background

Previous experience evaluating AI-generated code or participating in language-model tuning is helpful. It can support your ability to recognize model failure patterns, design effective test cases, and provide useful feedback during evaluation workflows.

• Experience with AI-generated code evaluation
• Experience participating in language-model tuning
• Familiarity with reinforcement learning from human feedback workflows

Why Do AI Training Work

AI training and data-labeling work offers a way to apply specialized technical knowledge to the development of state-of-the-art AI systems. Contributors help shape how models understand and generate code while working remotely with flexible project structures.

• Remote work that can fit around other commitments
• A direct role in improving modern AI systems
• An opportunity to build experience in a rapidly growing technology industry
• Flexible part-time work with a 20+ hour weekly commitment for this project

How to Apply Through OpenTrain

Create a free OpenTrain account and build a profile that reflects your CUDA, C++, Python, PyTorch, NumPy, and code-evaluation experience. Apply through OpenTrain to be considered for this contractor opportunity.

• Prepare a profile highlighting relevant programming experience
• Show your experience with CUDA kernels, GPU parallelism, and scientific Python
• Describe any background evaluating AI-generated code or language-model outputs
• Apply through OpenTrain for the next steps