Java LLM Evaluation Engineer

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. OpenTrain helps contributors build a lasting profile, discover opportunities across the industry, and grow their experience in a rapidly developing field.

• Worldwide opportunity with applications handled through OpenTrain
• Part-time contractor engagement requiring 20+ hours per week
• A chance to build experience across software development and AI training

About AI Training and LLM Evaluation

AI training is the human side of building modern artificial intelligence. Engineers, annotators, and subject-matter experts prepare examples, review model outputs, and provide feedback that helps AI systems become more useful, accurate, and aligned with user needs.

In this role, your software engineering knowledge will support evaluation of dialog agents and large language models. Your judgments, technical explanations, datasets, and code contributions can help improve systems used for education, entertainment, and general question answering.

• Work directly with code evaluation, response ranking, supervised fine-tuning, and RLHF
• Help assess relevance, clarity, technical accuracy, user alignment, and ethical standards
• Contribute to cutting-edge AI development through flexible remote work

The Role

OpenTrain AI is seeking a Java LLM Evaluation Engineer to develop and maintain high-quality backend code for AI model training and optimization. The role combines practical Java development with hands-on evaluation of dialog agent systems.

You will assess model responses against defined criteria, explain your decisions, create task-specific training data, and help improve evaluation strategies. You will also contribute to supervised fine-tuning and reinforcement learning from human feedback, including work related to reward model refinement.

• Role: Java LLM Evaluation Engineer
• Engagement: Part-time contractor
• Time requirement: 20+ hours per week
• Experience level: Entry level
• Work location: Worldwide
• Working language: English

What You'll Do

You will combine backend engineering, software quality practices, and structured AI evaluation. Clear technical reasoning and careful attention to evaluation criteria will be important throughout the work.

• Design, develop, and maintain efficient Java and backend components for LLM training and optimization.
• Benchmark model performance, analyze evaluation results, and support continuous improvement.
• Evaluate and rank model responses to user queries using predefined criteria.
• Write clear technical explanations for response rankings and evaluation decisions.
• Create and maintain high-quality datasets for supervised fine-tuning.
• Collaborate with researchers and annotators on RLHF and reward model refinement.
• Create and refine model responses for clarity, relevance, and technical accuracy.
• Review code and documentation for quality, security, stability, readability, and testing practices.
• Help improve evaluation processes through new tools and methodologies.

Required Skills and Qualifications

You should be comfortable writing practical Java and working with backend development concepts. The role requires strong English communication and the ability to follow detailed evaluation criteria while documenting technical judgments clearly.

A bachelor's or master's degree in engineering or computer science, or equivalent experience, is appropriate. Prior software quality assurance or test planning experience and experience evaluating model responses or creating training data are helpful.

• Proficiency with Java syntax, conventions, and practical backend development
• Ability to produce clear, correct, well-organized, and clearly annotated code
• Experience building modular web applications with scalable architectures
• Knowledge of testing, security, stability, readability, and code review practices
• Experience evaluating and ranking AI model responses or writing technical rationales
• Understanding of supervised fine-tuning, RLHF, reward models, and task-specific datasets
• Strong written and spoken English communication
• Ability to follow detailed evaluation criteria consistently

Who Should Apply

This opportunity may suit an entry-level software engineer, Java developer, QA professional, or technically minded AI contributor who wants to apply programming and evaluation skills to real model-improvement work. You do not need a separate AI-training career history if you can demonstrate the required Java, backend, communication, and analytical abilities.

• Java developers interested in large language model evaluation
• Backend engineers who enjoy testing, reviewing, and improving technical systems
• QA or test-planning professionals with strong software quality instincts
• Contributors who can explain why one model response is better than another
• Engineers interested in building a long-term portfolio in AI training

How to Apply Through OpenTrain

Create a free OpenTrain account and apply in minutes. Your OpenTrain profile can help you present relevant software, evaluation, and AI-training experience as you discover and pursue future opportunities in the field.

• Review the role requirements and prepare your Java and backend experience
• Highlight any work involving code review, testing, model evaluation, or training datasets
• Apply through OpenTrain for consideration as a part-time contractor
• Continue building your AI-training profile as your experience grows