CUDA and Python Code Evaluation Expert

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. OpenTrain AI hires and contracts specialists for projects that help shape how modern AI systems learn, reason, and perform.

As an OpenTrain contractor, you can build a profile around your AI training experience, discover projects that match your technical background, and apply in minutes. Creating an OpenTrain account is free.

About AI Training and Code Evaluation

AI training is the human side of building artificial intelligence. Technical experts review examples, write prompts, assess model responses, and correct generated code so that AI systems become more accurate, reliable, and useful.

This project focuses on large language model improvement through code translation, supervised fine-tuning data generation, and reinforcement learning from human feedback response evaluation. You will not build or fine-tune language models.

The Role

OpenTrain is seeking a remote CUDA and Python code evaluation specialist for a part-time contractor engagement of 20 or more hours per week. You will translate CUDA and C++ implementations into equivalent Python using PyTorch and NumPy, evaluate logical and performance parity, and provide detailed corrections to model-generated code.

The role is listed as entry level, while the technical requirements call for substantial professional experience. Candidates should have at least five years of overall professional experience, including at least three years with Python and at least two years with CUDA and C++.

• Work remotely from India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Türkiye, Brazil, or Mexico.
• Work as a contractor on a part-time schedule of 20 or more hours per week.
• Use English for written and conversational technical communication.

What You'll Do

You will analyze GPU-accelerated code and create technically accurate training and evaluation materials. Your work will require careful judgment about correctness, numerical consistency, performance, parallelism, and code quality.

You will also explain technical decisions clearly, maintain documentation for reproducibility, and identify recurring failure patterns that can guide improvements to model-generated code.

• Analyze CUDA kernels and GPU-accelerated code for structure, function, efficiency, and parallelism.
• Translate CUDA and C++ implementations into readable, correct Python with PyTorch and NumPy.
• Review generated code translations for logical, numerical, performance, and consistency issues.
• Create prompts and test cases based on real-world CUDA and PyTorch programming tasks.
• Rank model responses and explain the technical reasoning behind your judgments.
• Debug translated code and recommend improvements based on recurring model failure patterns.
• Maintain clear documentation that supports reproducibility.

Required Skills and Experience

This role requires strong hands-on programming ability and a practical understanding of GPU computation. You should be able to reproduce CUDA kernel behavior accurately in Python while preserving numerical consistency and communicate detailed technical feedback in clear English.

Experience evaluating AI-generated code or contributing to language model tuning is helpful, but the core requirements are expertise in Python, CUDA, C++, PyTorch, NumPy, debugging, and performance-aware programming.

• At least five years of overall professional experience.
• At least three years of professional Python experience.
• At least two years of CUDA and C++ experience.
• Strong Python skills for scientific computing with PyTorch and NumPy.
• Solid understanding of CUDA programming concepts and C++ fundamentals.
• Strong knowledge of GPU computation, parallelism, and performance-aware coding.
• Ability to analyze CUDA kernels and reproduce their behavior in Python.
• Strong debugging skills and attention to code quality.
• Clear written and conversational English communication.

Who Should Apply

This opportunity is well suited to software engineers, computer scientists, and GPU programming specialists who can assess whether code is both functionally correct and computationally efficient. It may also appeal to developers interested in applying their technical judgment to the rapidly growing field of AI training.

If you can move confidently between CUDA, C++, Python, PyTorch, and NumPy, explain nuanced code-level decisions, and work independently on detailed evaluations, this project offers a way to contribute directly to how advanced AI systems handle programming tasks.

• CUDA developers with strong Python and scientific-computing experience.
• C++ or GPU engineers comfortable evaluating equivalent implementations.
• Python specialists with practical knowledge of PyTorch, NumPy, and parallel computation.
• Technical contributors who can provide precise, well-reasoned feedback on model outputs.

Why Work in AI Training

AI training and data-labeling work is a fast-growing part of the technology industry. Contributors help prepare and review the examples that modern AI models use to learn, including programming tasks, written responses, images, audio, and other data.

Many AI training projects are remote and flexible, allowing specialists to choose work that fits their schedules while contributing to cutting-edge systems. Technical projects can also help you build a focused portfolio of experience in an expanding field.

How to Apply Through OpenTrain

Create a free OpenTrain account, complete your profile with your CUDA, C++, Python, PyTorch, and NumPy experience, and apply for this contractor opportunity. Highlight relevant code evaluation, debugging, GPU programming, or AI training work so your technical background is easy to assess.

• Confirm that you are located in one of the listed eligible countries.
• Showcase your professional experience and programming specialization.
• Indicate your availability for 20 or more hours per week.
• Apply through OpenTrain in minutes.