Senior Software Engineer — AI Evaluation & Benchmarks | Remote Contract | $80–$100/hr

@Mahihassi

With over four years of professional software engineering experience, and a strong focus on AI development and backend systems, I am confident in my ability to meet the needs of this project. I'm particularly skilled in designing coding benchmarks and building scalable evaluation and data processing pipelines, which I believe will be valuable in evaluating and analyzing AI-generated software for reliable code generation. Beyond my technical skills, I am adept at working with large code repositories and multi-language development environments, as proven by my proficiency in Python, JavaScript/TypeScript, Go, C++, Java, and Rust – all languages that could be utilized in this role. Additionally, my experience with Git and version control workflow is crucial for maintaining accurate records of the project's progress. What sets me apart as a freelancer though is my passion for quality assurance; I thrive on finding subtle bugs and refining edge cases. Being part of this project would mean more than just a job. It would be an opportunity to contribute towards the improvement of advanced AI systems while working autonomously but collaboratively with your team.

@DeveloperStation

Hi there, I’ve spent the last 15 years building large-scale web apps and leading teams, with a strong focus on AI and machine learning in the last 5 years. I’ve developed production-ready LLM products and worked extensively with Python, FastAPI, and CI/CD pipelines. At my previous startup, we created an AI-powered product that helped developers write better code by analyzing their GitHub repositories and providing actionable insights. We also built a Chrome extension that integrated with VS Code to deliver real-time suggestions while developers wrote code. I’m passionate about using AI to enhance developer productivity and have a strong understanding of what makes a product truly valuable. Let’s schedule a 10-minute introductory call to discuss your project in more detail and see if I’m the right fit for your needs. I’m looking forward to hearing more about this exciting opportunity. Best, Adil

@GdevDataSceince

Hi there, I am a Data Scientist and am a professional responsible for extracting actionable insights and knowledge from large volumes of data. As an experienced Data Scientist in the field of machine learning, I am highly proficient in Python and have a deep understanding of algorithms and data structures. My skills make me a great fit for your project as I can guide you through comprehensive coverage of data structures and algorithms while providing patient and thorough explanations. I have over 12-plus years of experience with Python Library Pandas, Karas, TensorFlow, NumPy, PyCharm, Py torch, Open CV, NLP, and others. With over a decade's worth of experience under my belt, including expertise in NLP, Neural Networks, CNNs, RNNs, LSTM, GANs just to mention a few, I can provide you not only with knowledge but also how to apply it efficiently. Partnering with me ensures you have a patient, knowledgeable and skilled tutor who is dedicated to your success in this field. My top priority is to provide a high quality of work, https://www.freelancer.com/u/GdevDataSceince Let's discuss this further via chat, and I'll start your project right now. Thanks Gdev

@OutsourceMan

⭐⭐⭐⭐⭐ Project Proposal for AI Evaluation & Benchmarks CnELIndia team proposes to deliver high-quality support for your Senior Software Engineer role in AI evaluation and benchmarking. With 5+ years average experience in Python, large codebases, and scalable systems, our engineers align closely with your needs. Key Offerings: Design and implement robust coding benchmarks and evaluation frameworks for LLMs. Build scalable data pipelines, CI/CD integrations, and automated testing systems. Analyze AI-generated code for correctness, efficiency, edge cases, and failure patterns. Provide expert debugging, Git workflows, and multi-language repository handling. How CnELIndia Team Helps: Assign dedicated remote senior engineers immediately for full-time availability. Conduct initial 3-month contract with weekly progress reports and flexible extensions. Collaborate on benchmark methodology, model assessment, and actionable feedback. Ensure independent delivery with strong English communication and production-grade standards. We can start within days. Please share next steps for technical discussion. (748 characters)

@alizain721

You want rigorous, production grade benchmarks and pipelines that expose how models fail on real world code not just toy metrics. I build evaluation systems that scale and produce actionable failure signals for engineering teams. The hidden problem is often brittle tooling and unclear pass criteria which make results irreproducible and hard to act on. Fixing that requires solid pipelines, deterministic tests, and careful dataset engineering. Seven years software engineering experience. Python is my primary tool for evaluation scripts, data pipelines, and test harnesses. Built Practice Tool AI, an AI driven feedback engine deployed on AWS with automated pipelines and monitoring that processed model outputs end to end. My practical approach is simple and incremental: I will create reproducible evaluation jobs and lightweight runners for multi language snippets I will instrument tests to measure correctness reliability performance and edge cases I will wire results into dashboards and CI so benchmarks run on every change If you have a repo please grant read access or share current benchmark artifacts so I can prepare a one week plan. Which repo or sample benchmark should I review first?

@SkillCrafts

I noticed your need for a Senior Software Engineer to build AI evaluation frameworks and coding benchmarks. My recent work involved developing a robust testing suite for LLM-generated code, achieving a 95% accuracy rate in identifying functional correctness and adherence to style guides, directly mirroring your requirement for rigorous evaluation systems. My technical approach will leverage Python with libraries like Pytest and Hypothesis for unit and property-based testing of AI-generated code. For large-scale data pipelines, I'll utilize Apache Beam and cloud-native services (e.g., AWS Lambda, S3, EMR) to efficiently process and analyze benchmark results. I will design a modular framework allowing for easy integration of new evaluation metrics and AI models, ensuring scalability and maintainability. How are you currently approaching the generation and validation of diverse test cases for your benchmarks? What are the primary metrics you're prioritizing for evaluating AI-generated software quality? I'm keen to discuss how my experience can directly address these challenges; let's schedule a brief call.

@photop2

✅✅✅✅✅ It's My Best Pleasure to SUPPORT You ✅✅ cost: 95 USD/hr, duration: Ongoing when need I can complete this project wonderfully, contributing to advanced AI evaluation and benchmarking systems with a strong focus on scalable infrastructure, rigorous software assessment, and production-grade engineering practices. My expertise includes Python backend development, large-scale code analysis, benchmarking pipelines, debugging complex systems, and designing reliable evaluation frameworks for AI-generated code. From my experience, effective AI evaluation systems depend heavily on reproducible benchmark design, structured failure analysis, scalable data processing pipelines, and precise edge-case testing to accurately measure reasoning, debugging, and software quality across diverse codebases. I have experience working with large repositories, CI/CD workflows, automated testing systems, Git-based collaboration, and scalable backend architectures. I am also comfortable analyzing AI-generated outputs for correctness, efficiency, maintainability, and hidden failure patterns while delivering actionable technical feedback for continuous improvement. I am confident I can contribute effectively to your AI benchmarking initiatives and help build reliable, high-impact evaluation systems for next-generation intelligent software models. Pier M

@markupdudes

Hi, I am excited about the opportunity to contribute as a Senior Software Engineer on your AI evaluation and benchmarking project. With over 4 years of professional software engineering experience, predominantly in Python, I have developed robust and scalable backend systems and extensive expertise in working with large codebases. My background includes designing evaluation frameworks and building automated testing pipelines which aligns perfectly with your requirements. I am confident that my skills in debugging, CI/CD implementation, and deep understanding of software architecture will help build precise benchmarks and data pipelines to rigorously assess AI-generated code for correctness, reliability, and edge cases. I am fully equipped to collaborate remotely and independently while delivering high-impact solutions that enhance AI coding performance. I propose to start with a thorough project scoping and initial framework design over the first week, followed by iterative development and testing cycles. I am ready to engage full-time for the initial 3-month contract with flexibility for possible extensions Could you please clarify which AI models and programming languages will be the primary focus for the benchmarks? Best regards,

@KrisuTechkul

Hi, we are a team of 20+ AI/ML Engineers based in Delhi - have completed 300+ projects with 100% client satisfaction & long term association. With a sharp focus on AI and software development, my team and I are well-positioned to make impactful contributions to your project. Over the past 4+ years, we've honed our Python expertise and become intimately familiar with working with large codebases, designing benchmarks, and building scalable data pipelines. These skills make us expertly equipped to tackle the intricate tasks required for your AI evaluation and benchmarking initiatives. Moreover, our experiences extend beyond just coding; we value both the performance and reliability of software systems. This has fueled our pursuits in continuous integration/deployment (CI/CD) as well as automated testing frameworks-both of which are directly applicable to your project. Furthermore, our comprehensive understanding of Git and version control workflows positions us uniquely to handle the complexities of multi-language development you require.

@dataspro

Hello! As a Senior Software Engineer with a strong background in AI evaluation and benchmarks, I believe I can bring valuable expertise to your project. I am proficient in both Spanish and English, ensuring clear communication and understanding throughout the development process. Looking forward to the possibility of collaborating with you on this exciting opportunity. Thank you!

@jamshaiddev

Hi, I can contribute to AI evaluation and benchmarking systems by building scalable evaluation pipelines, coding benchmarks, and technical assessment frameworks focused on measuring reasoning quality, debugging capability, reliability, and production-level code generation. With strong software engineering experience across Python, backend systems, API architecture, large codebases, CI/CD workflows, and scalable infrastructure, I can help design benchmark methodologies, analyze AI-generated code quality, identify failure patterns, and build reliable evaluation systems that improve model performance. I have experience working with structured engineering workflows, Git-based collaboration, testing practices, debugging complex systems, and building maintainable architectures designed for long-term scalability and performance. I am comfortable contributing across benchmark design, evaluation pipelines, backend infrastructure, automated testing, and AI system analysis within remote engineering environments. Best regards, Muhammad Jamshaid

@rishidarkunde

With a proven track record spanning over 9 years of professional software engineering experience, my contribution to your AI evaluation and benchmarking project will be invaluable. I have witnessed the power of AI in transforming codes into intelligent systems, which makes this project truly intriguing to me. My expert-level Python development skills, experience with large codebases and software architecture, as well as my ability to develop evaluation frameworks that improve coding performance are perfectly aligned to meet the complex and extensive requirements of your project. I strongly believe that the quality of my work should speak for itself. Prior to hitting "send", my codes go through rigorous testing, reasoning out bugs, ensuring reliability, efficiency while handling edge cases properly. From designing coding benchmarks to analyzing AI-generated code and providing timely technical feedbacks, my skills have been honed to meticulously ensure top-notch results with impeccable quality. This opportunity is much more than just another project for me. It is a chance to contribute to furthering the capabilities of advanced AI systems. I genuinely want to be an integral part of projects that make a real-world impact and collaborate with topnotch professionals like yourselves. My commitment is unswerving till the final delivery is satisfactory surpassing all your expectations - just as you deserve it!

@thetechnicalhunt

The hard part of a coding benchmark is not running the harness, it is designing tasks where a passing score actually means the model reasoned, not pattern-matched a memorized solution, and where a silent failure (a plausible-looking diff that breaks an untested edge case) gets caught rather than scored as correct. Contamination, flaky graders, and reward-hacking are where most eval suites quietly mislead. With 15 years of experience, I work as a true TeamOfOne, the single accountable owner across design, engineering, and QA, from raw task spec to a benchmark a research team trusts. At Fold Health, as Co-Founder and Principal Architect, I ran a production LLM stack at 200M+ tokens a month where an eval harness gated every prompt change: regression suites, per-claim scoring, source-span provenance, and a failure-mode inventory that blocked deploys on quality drift. At Praxify (founding engineer, acquired by athenahealth for $64M) I worked large multi-language codebases at scale. Experience: 15 years, expert Python, large-codebase and pipeline work daily, Git/CI/CD and automated testing as baseline. Public GitHub is light (NDA healthcare code); happy to walk through architecture on a call or a short paid trial benchmark. Ready to get started. Best, Kaustubh

@Appworldz

This is exactly the intersection I enjoy most: large-scale software engineering + AI evaluation rigor. I’ve worked on production backend systems, benchmark-style evaluation pipelines, automated testing frameworks, and AI-assisted code analysis where correctness, edge-case detection, and scalability mattered more than flashy demos. My strongest fit here is around Python infrastructure, benchmark/evaluation design, repository analysis, CI-integrated testing pipelines, and identifying subtle model failure patterns in generated code. I’m also comfortable navigating large multi-language codebases and building structured assessment workflows that measure reasoning quality rather than superficial pass/fail outputs. Availability: full-time remote Rate: $90–100/hr Open to technical assessment and long-term extension.

@raj00565

With 12+ years of experience in DevOps, system administration, and backend development, my team and I specialize in building scalable, reliable, and AI-driven solutions using Python, AWS, GCP, CI/CD, and cloud infrastructure. We have hands-on experience working with AI/ML evaluation systems, large codebases, and performance benchmarking, helping identify model failures, edge cases, and optimization opportunities. Beyond technical expertise, we value clear communication, fast problem-solving, and long-term collaboration. We’re excited about the opportunity to contribute to meaningful AI innovation and deliver reliable, high-quality results from day one.

@AnderSun

I propose to contribute as a Senior Software Engineer focused on AI evaluation and benchmarking systems. I will help design and implement robust coding benchmarks, build scalable evaluation pipelines, and analyze AI-generated code for correctness, edge cases, and performance. With 17+ years of experience in large-scale system debugging, Python/backend development, and multi-language codebase engineering, I can quickly identify model failure patterns and translate them into actionable improvements. I also have hands-on experience with LLM systems, AI agents (LangChain/Dify), and runtime analysis tools, which aligns closely with rigorous AI model evaluation and debugging workflows.