AI Training Platform Software Engineers

We are seeking experienced Software Engineers with hands-on experience working on AI training platforms, data annotation projects, and Large Language Model (LLM) evaluation workflows. The ideal candidate has completed projects or worked as an AI coding expert, software engineering evaluator, AI trainer, or technical annotator through platforms such as DataAnnotation, Handshake, AfterQuery, Mercor, Outlier, micro1, or similar AI training companies. We are particularly interested in engineers who understand how to evaluate AI-generated code, solve complex programming problems, review technical responses, and improve the quality, accuracy, and reliability of AI models. This opportunity is ideal for engineers who combine strong software development skills with practical experience in AI training, coding assessments, and LLM evaluation. Key Responsibilities - Complete and evaluate software engineering tasks used to train and improve AI models. - Review AI-generated code for correctness, efficiency, readability, security, and adherence to best practices. - Solve complex programming challenges and provide high-quality reference solutions. - Evaluate AI model responses to coding, debugging, system design, and software architecture questions. - Identify errors, edge cases, logical inconsistencies, and weaknesses in AI-generated solutions. - Write clear technical explanations, code reviews, and structured feedback. - Create, validate, or improve coding problems, test cases, rubrics, and evaluation criteria. - Work with programming languages, frameworks, databases, APIs, and development tools relevant to your expertise. - Follow project guidelines, quality standards, and deadlines while maintaining accuracy and consistency. Required Qualifications - Professional experience as a Software Engineer, Full-Stack Engineer, Backend Engineer, Frontend Engineer, or related technical role. - Demonstrated hands-on experience with at least one AI training, coding evaluation, or data annotation platform, such as DataAnnotation, Handshake, AfterQuery, Mercor, Outlier, micro1, or an equivalent service. - Strong programming and debugging skills in one or more languages, such as Python, JavaScript/TypeScript, Java, C++, Go, or C#. - Experience reviewing, testing, debugging, or evaluating code written by other developers or AI systems. - Solid understanding of algorithms, data structures, software engineering principles, and testing methodologies. - Ability to explain technical concepts clearly and identify subtle errors in code. - Strong written communication, attention to detail, and independent problem-solving skills. Preferred Qualifications - Experience contributing to AI coding, LLM training, model evaluation, or reinforcement learning from human feedback (RLHF) projects. - Experience writing prompts, assessing model outputs, ranking responses, or creating evaluation rubrics. - Familiarity with automated testing, unit testing, integration testing, and code quality tools. - Experience with APIs, databases, cloud services, distributed systems, or full-stack application development. - Experience evaluating AI-generated solutions for correctness, performance, maintainability, and security. - A portfolio, sample work, or verifiable description of relevant AI training projects. Application Requirements - Please include the following information in your proposal: 1. Professional Background: Briefly describe your software engineering experience, including your primary programming languages, frameworks, and technical specialties. 2. AI Training Platform Experience: Which platforms have you worked with? Please specify DataAnnotation, Handshake, AfterQuery, Mercor, Outlier, micro1, or any other relevant platforms. Project Types: What types of tasks have you completed? Examples include coding evaluations, AI response ranking, code generation, debugging, software engineering assessments, data annotation, and LLM evaluation. 3. Experience Duration: Approximately how long have you been working on AI training or coding evaluation projects? 4. Technical Expertise: Which programming languages and technical areas can you confidently evaluate or work with? 5. Availability: How many hours per week can you commit, and what is your general availability? NOTE: My minimum expectation is 8 hours/day, and you also need to work on weekends if possible 6. Relevant Experience: Share a brief example of a challenging technical task you completed as part of an AI training or evaluation project. Do not share confidential project materials or proprietary assessment content. - Engagement Details Job Type: Contract / Freelance Work Arrangement: Remote Experience Level: Intermediate to Expert Project Duration: To be discussed based on project requirements and candidate fit Workload: Flexible, depending on availability and project needs How to Apply If you have strong software engineering skills and practical experience with AI training platforms, we would like to hear from you. Please submit a proposal answering all seven application questions above. Candidates with relevant hands-on experience, strong technical judgment, and a demonstrated ability to evaluate AI-generated code will receive priority consideration. We are looking for engineers who can demonstrate both real software development expertise and a clear understanding of AI training and evaluation workflows.