Software Engineering AI Trainer | Earn up to ₹4,00,000/month | Remote

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@ixorawebmob

Hello, I’ve gone through your project details, and I believe this is something I can definitely contribute to. With over 10 years of experience in software engineering and expertise in Python, JavaScript, and system-level challenges, I can help design and evaluate realistic coding tasks for AI development. My background in full-stack development, combined with hands-on experience in debugging and code review, positions me well for this consulting role. I focus on problem-solving and delivering high-quality, production-realistic solutions. I’m particularly excited about the opportunity to enhance large language models and the real-world impact this role offers. I have a solid track record of crafting clear natural-language specifications and ensuring robust test coverage, vital for ensuring alignment between code and expected outputs. Here is my portfolio: https://www.freelancer.in/u/ixorawebmob Could you elaborate on the kind of projects you foresee and any particular areas of focus for the AI training role? Let’s discuss how I can contribute effectively to your projects over chat! Regards, Arpit Jaiswal

@ashinnd84

Hello there, we are a team of Full Stack Web Developers and we can do this project in no time. Thanks Ashish Kumar.

@teamsoul234

Hello, I’m very interested in the Software Engineering AI Trainer role. I have solid experience in Java, Spring Boot, and backend system design, along with hands-on work in debugging production issues, refactoring code, and building scalable systems. I regularly work with multi-file codebases, write clean and testable code, and create unit/integration tests using JUnit. I’m comfortable reviewing code, identifying edge cases, and improving performance and structure in real-world applications. I also have experience working on API integrations, system design, and handling complex backend workflows, which aligns well with creating realistic engineering tasks and evaluations. My approach: * Design practical, real-world coding scenarios (bug fixes, features, refactoring) * Write clear specifications and structured solutions * Ensure strong test coverage and validation * Provide detailed and actionable peer reviews I’m comfortable working independently, managing time effectively, and maintaining high-quality output. I’m excited about contributing to improving AI systems with real engineering insights. Best regards, Dharmender Kumar

@habebaftooh

I have already worked on very similar AI trainer / software engineering evaluation tasks with an AI consulting company based in Dubai, where my role involved reviewing AI-generated outputs, evaluating code quality, debugging implementation issues, writing structured feedback, and improving the reliability of AI-assisted workflows. So this project is very aligned with the type of work I have already been doing. I studied Artificial Intelligence for 4 years during my Bachelor’s degree, and over the past year I have been working hands-on as an AI Engineer / AI Developer on real client projects involving Python, backend systems, automation, model pipelines, LLM integrations, data processing, and production-style debugging. Some examples of relevant work I have done include building AI automation systems for document and invoice processing, where I used OCR and LLMs to extract structured data, validate outputs, handle edge cases, and create reliable workflows for business operations. I also worked on a sign-language pose synthesis project where I had to debug and adapt a multi-file research codebase, clean and preprocess pose datasets, run training pipelines, evaluate generated outputs, compare model results, and document limitations clearly for the client’s technical team.

@kishanprasadtech

Hi, I’m a full-stack developer with 5+ years of experience working on production-grade applications using Java, JavaScript, and typescript. My work often involves debugging complex, multi-module systems, implementing features, and ensuring code quality through structured testing and reviews. **Relevant experience for this role:** * Designing and implementing backend systems (Spring Boot, Node.js) with clean architecture * Writing and reviewing multi-file codebases with a focus on scalability and maintainability * Creating unit and integration tests using JUnit * Debugging legacy systems and handling refactoring/migration tasks * Writing clear technical specifications and translating them into working implementations **How I can contribute:** * Create realistic, high-quality coding tasks (bug fixes, feature builds, refactors) * Develop strong reference implementations with proper edge-case handling * Build robust test suites to validate correctness * Provide detailed, actionable peer reviews focused on real-world scenarios I’m comfortable working independently, managing timelines, and maintaining high-quality output across tasks. The project-based, flexible nature of this role fits well with my current workflow. I’d be happy to take on a sample task or evaluation to demonstrate my approach. Thanks, Kishan

@mapcoresoftech

Hi, This role aligns closely with my work. I’m a Lead Java Engineer and AI Systems Architect with 17+ years of experience in distributed systems and, more recently, AI platforms using LLMs, RAG pipelines, and agent-based workflows. I’ve built and led large-scale systems using Spring Boot, Kafka, Spark, and Snowflake, and have hands-on experience designing AI-driven solutions including chat systems, evaluation workflows, and multi-agent architectures. Your focus on designing multi-file tasks, evaluating edge cases, and aligning specs with real-world behavior strongly resonates with my experience. I’ve spent years debugging complex systems, refactoring legacy code, and ensuring production-grade quality across enterprise platforms. I bring: Strong expertise in Java, Python, and backend systems Deep experience in unit/integration testing and validation Practical exposure to prompt design, LLM evaluation, and system reliability Ability to create clear specs and review outputs with a real-world engineering lens I’m particularly interested in improving LLM code generation through structured tasks and rigorous evaluation. Available ~20 hrs/week. Happy to start with a pilot task. Looking forward to contributing.

@adamw368

Hi, your AI trainer role caught my attention because building real software tasks for LLM evaluation is the kind of engineering work I enjoy. Recently, I helped create code review and test tasks for a Python and TypeScript backend project, where my role was to write specs, fix hidden bugs, add pytest and Jest tests, and review other engineers’ answers. The hardest part was making tasks realistic but still fair, and my first simple checklist missed edge cases, so I moved to a rubric with expected behavior, failure cases, and test proof because it gave cleaner reviews than loose comments or only unit tests. For this work, I would focus on clear task specs, multi file bugs that look like real production issues, and tests that catch both normal paths and tricky edge cases. I can also review peer work for unclear wording, weak tests, or code that passes by chance instead of by design. Do you prefer contributors to create tasks from existing repositories, or should we build small self contained codebases for each evaluation task? I can start with a small task sample and share how I would structure the spec, solution, tests, and review notes. Best, adam

@Solutionzhere

Hi, this aligns perfectly with our AI evaluation and engineering practice at SolutionzHere. We have senior engineers (5–10 yrs) experienced in Python/JS/TS, multi-file systems, test design (pytest/Jest), code reviews and LLM evaluation workflows. We’ve built realistic task sets, reference implementations and scoring rubrics for AI training pipelines. We can contribute high-quality task design, peer review, edge-case analysis, and validation suites with consistent output quality. Rate aligns—₹2,500–₹4,000/hr, flexible 20 hrs/week. We’ve supported similar AI training initiatives at scale. One question: do you follow a fixed evaluation rubric framework or will we help define it from scratch?

@vf78

Hello, I bring a lot of experience in Software Development and Project management. I have worked on complex Enterprise systems that have been successfully running in production. I have experience in cloud-based machine learning which we used for data extraction, classification and analysis from unstructured documents. I have proficiency in Java, Python, Javascript. I would like to discuss how i can contribute to this project. My availability: 30 hrs

@rhythmfeb2008

I offer a specialized background that combines production-grade Software Development Engineer (SDE) and SDET experience with an academic and practical focus on Artificial Intelligence and Machine Learning. This dual perspective is critical for the "AI Trainer" role, as I possess the mindset required to both build complex systems and rigorously evaluate the "reasoning" of Large Language Models.

@bijenderk5

Hi, I understand this role requires designing real-world, multi-file engineering tasks—I have strong experience in .NET, JavaScript/TypeScript, and backend systems, including debugging, refactoring, and writing production-level code. I can create structured specifications, reference implementations, and robust test suites (pytest/Jest/xUnit) aligned with real scenarios. I’m comfortable reviewing complex codebases, identifying edge cases, and providing clear, actionable feedback. My approach focuses on realism, clarity, and strong alignment between specs, code, and expected outputs. I’m available for part-time, high-quality contributions and can start immediately.

@vaishnavik578

I bring strong experience in backend and full-stack development with Python and JavaScript, along with hands-on work in debugging complex codebases, writing tests, and performing detailed code reviews. My background in AI data labeling and working with structured tasks gives me an edge in designing realistic, high-quality evaluation scenarios aligned with LLM improvement goals. My methodology focuses on building production-grade tasks with clear specifications, robust reference implementations, and comprehensive test coverage, while systematically identifying edge cases and failure modes. I emphasize clarity, reproducibility, and alignment between requirements, code, and expected outputs. I am comfortable working independently in a freelance setup, managing time effectively, and delivering high-quality results within flexible schedules. My experience with reviewing and improving technical outputs ensures I can contribute both as a creator and evaluator of engineering tasks. With a strong foundation in software engineering principles and growing exposure to AI evaluation workflows, I am well-positioned to contribute meaningfully to improving large language model performance through precise, real-world coding tasks.

@Satisfiesdream

I am an experienced software engineer with a strong background in QA automation, manual testing, API testing, and database validation. I have worked across multiple domains including implementation engineering, business analysis, and quality assurance, giving me a well-rounded perspective on real-world software systems. I have hands-on experience designing test suites, identifying edge cases, reviewing code quality, and working with multi-file codebases. My practical exposure to debugging, test generation, and structured documentation aligns well with the task design and peer review responsibilities outlined in this role. I am highly detail-oriented, comfortable working independently, and capable of producing clear, structured technical specifications and reference implementations. I understand what production-realistic code looks like and can evaluate submissions for correctness, clarity, and real-world relevance. I am eager to contribute to AI model improvement through high-quality engineering tasks and evaluations. This role aligns perfectly with my goal of deepening my expertise in AI systems while delivering consistent, quality output. I am India-based, available for remote work, and can commit approximately 20 - 40 hours per week on a flexible schedule. I look forward to contributing meaningfully to your platform. Also I'm part of MLOPS and ETL testing.

@Subham3001

Hi, This role aligns very well with my experience and interests—especially working on complex backend systems, debugging multi-file codebases, and designing production-level solutions. I have 3+ years of experience in Java backend development using Spring Boot, microservices, and REST APIs, along with hands-on work in debugging, refactoring, and building scalable systems. I’m comfortable working across large codebases, identifying edge cases, and ensuring clean, maintainable implementations with proper testing. I’ve also worked on event-driven systems (Kafka/JMS), API design, and integration layers, which gives me a strong foundation for designing realistic engineering tasks and evaluating system behavior beyond surface-level coding. What I can contribute: • Designing real-world coding tasks (bug fixes, features, refactoring) • Writing clear specifications with aligned implementations • Creating and extending unit/integration tests • Reviewing peer submissions for correctness and quality • Identifying edge cases and failure scenarios I enjoy structured problem-solving and can maintain high-quality output with consistency. I’m comfortable working independently, managing timelines, and adapting to evolving project requirements. Looking forward to contributing to improving LLM performance through real-world engineering tasks. Regards, Subham

@ashishhardiya10

With over 9 years of experience in software engineering, I strongly believe that I possess the skills and expertise needed to excel in your AI Trainer project. My proficiency in both Java and JavaScript perfectly aligns with your requirements, and my understanding of full-stack development allows me to think holistically when faced with complex coding tasks. In addition to my technical abilities, my natural-language writing skills have proven valuable in creating clear, structured specifications needed for this role. Drawing upon my experience with multiple domains including banking, healthcare, logistics etc, I have developed strong debugging and code-navigation abilities, essential when working with large, multi-file codebases as stipulated in your project details. Moreover, my familiarity with evaluation and benchmarking procedures strongly correlates with your requirement for defining solution trajectories and writing evaluation rubrics. I commit to delivering not just high-quality coding tasks, robust reference implementations and rigorous testing coverage but also providing actionable peer review feedback that aligns with your mission of ensuring strong specification-code-output reliability. By choosing me as your consultant, you gain a diligent professional who consistently exceeds expectations. Let's collaborate to revolutionize the software industry through the power of AI!

@shokoufeh1994

I'm a software engineer with experience across Python, C#, Node.js, and TypeScript, and I understand how AI training data works from a technical standpoint. I've written code-focused prompts, evaluated code completions for correctness, and produced preference rankings for coding tasks. For software engineering AI training, I can write accurate code snippets, debug examples, and detailed explanations across multiple languages. I know what clean, idiomatic code looks like vs. what subtle bugs or bad patterns look like — which is exactly the signal needed for training. What languages and coding domains are you prioritizing for this batch of training data? I want to make sure my background aligns well before we start.

@bhuiyanesmay

I’m applying for the Software Engineering AI Trainer role as a freelance consultant. I have strong backend and full-stack experience working with complex, multi-module systems and optimizing real-world applications. I’ve contributed to enterprise HRMS and e-recruitment systems, designing features, improving bulk performance, and refactoring legacy code to enhance scalability. I’ve also worked on government applications using Spring Boot and Django-based frameworks, focusing on performance tuning and clean system design. I’m comfortable creating realistic engineering tasks, including bug fixing, feature development, and refactoring across multi-file codebases. I write clear specifications, build robust solutions, and optimize systems and databases efficiently. I also have experience with Remotasks, contributing to AI data annotation and evaluation. I analyzed outputs, ensured quality, and followed structured guidelines—gaining practical insight into improving AI model performance. I regularly engage in problem solving, code reviews, and knowledge sharing, with strong attention to edge cases and requirement alignment. I’m familiar with Agile workflows and tools like Jira. I’m available for part-time, project-based work and committed to delivering high-quality contributions. Best regards, Esmay Hassan Bhuiyan

@vaishnavia041

As a highly seasoned software engineer with over 10 years' experience, I consider myself well-prepared to take on the complexities of this AI Trainer role. My extensive background in software development and testing, specifically with technologies such as Python, JavaScript and SQL aligns perfectly with the technical requirements you seek. When combined with my proficiency in code review, debugging and navigation in complex code bases, these skills will enable me to design and evaluate realistic software engineering tasks to enhance large language models accurately. Moreover, having had prior exposure to data annotation, evaluation and structured labeling for AI or ML systems makes me thoroughly familiar with the kind of work that would be required in this position. Previously worked with AWS(EC2, Lambda, S3), Azure(AZ-104) and GCP(Pub/Sub) means I have experience of working with cloud services also. At my core, I am a problem solver with a logical mindset which allows me to identify edge cases, ambiguities and potential failure modes effectively conducting high-quality work. With the added advantage that I am India-based and adept at remote work further emphasizes why I am the right choice. Let's collaborate on taking your AI systems to new heights of intelligence through improved coding quality!