Software Engineering AI Training Expert

About OpenTrain

OpenTrain is the #1 platform for people building careers in AI training and data labeling. We help technical contributors find remote, flexible projects, consolidate proof of work in a single profile, and grow a durable freelance career teaching AI.

• Create a free OpenTrain profile to showcase your contributions and apply in minutes.
• OpenTrain connects you directly to hands-on AI training work where your technical skills shape model behavior.

Why AI training work matters

AI training (data labeling and human feedback) is the human side of building modern AI systems: people create examples, corrections, and expert solutions that models learn from. This work is remote, flexible, and a direct way to influence how models code, reason, and solve engineering problems.

• Work remotely from anywhere with a computer and internet connection.
• Flexible, part-time scheduling that fits around other commitments.
• Accessible pathways: domain expertise is often more important than prior AI experience.

The role

OpenTrain AI is hiring a Software Engineering AI Training Expert to design reproducible reinforcement-learning environments and reference solutions that test and improve AI models’ software engineering skills. This is a remote contractor position for 10–15 hours per week with hourly pay between $50 and $150 depending on experience.

• Position type: Remote contractor, part-time (10–15 hrs/week).
• Pay: $50–$150 per hour (hourly, USD).
• Work language: English. Open to contributors worldwide.

What you'll do

You will apply senior-level software engineering judgment to create training data and environments that push models on realistic engineering tasks. Your outputs will be reference implementations, challenge environments, and clear technical rationale that human reviewers and models can learn from.

• Design reproducible RL environments focused on code fixing, feature creation, refactoring, and optimization.
• Write expert-level code samples and debugging strategies in Python3, Java, Rust, Go, C++, or TypeScript.
• Analyze and resolve complex defects and performance bottlenecks across varied codebases.
• Implement new features with attention to scalability, maintainability, and best practices.
• Refactor and optimize legacy code to improve clarity and efficiency.
• Document technical reasoning and solution approaches to support high-quality training data.
• Review and validate peer-contributed code and technical submissions.

Requirements

You must be able to produce high-quality, expert-level engineering artifacts and explain your reasoning clearly. The role emphasizes hands-on software engineering skill and a track record of tangible contributions.

• Significant hands-on expertise in at least one: Python3, Java, Rust, Go, C++, or TypeScript.
• Deep understanding of algorithms, data structures, and software engineering principles.
• Proven ability to debug complex systems and deliver effective optimizations.
• Experience with large codebase refactoring and legacy system modernization.
• Track record of delivering high-impact features from conception to delivery.
• Strong documentation and communication skills.
• Active GitHub or GitLab profile with clear open-source contributions.
• Fluent English (reading and writing).

Who should apply

This role is ideal for senior software engineers who want to apply their craft to shape how AI systems learn to code and reason about complex systems. While prior AI experience is helpful, the core requirement is real-world engineering expertise and a portfolio of practical work.

• Senior engineers with hands-on experience in debugging, refactoring, and feature development.
• Engineers who enjoy clear technical documentation and mentoring via written solutions.
• Independent contractors who can commit 10–15 hours per week and work asynchronously.