About The Company
Turing is a leading technology company at the forefront of artificial intelligence and software development. Renowned for its innovative approach to AI research and development, Turing specializes in creating cutting-edge solutions that accelerate the advancement and deployment of powerful AI systems. The company is committed to fostering a dynamic and collaborative environment where talented professionals can contribute to transformative projects that shape the future of technology. With a global presence and a focus on remote work, Turing offers an inclusive workplace that values diversity, creativity, and continuous learning.
About The Role
We are seeking experienced software engineers at the tech lead level to join our innovative team working on large language model (LLM) evaluation and training datasets. This role involves engaging directly with high-quality public GitHub repositories to develop verifiable software engineering tasks based on real-world repository histories. The ideal candidate will have a strong background in software engineering, particularly in automation, issue triaging, and code quality assessment. Your expertise will contribute to building datasets that help train LLMs to solve realistic software engineering problems, expanding coverage across multiple programming languages and difficulty levels. This position offers an exciting opportunity to influence the future of AI-assisted software development while working on meaningful, impactful projects.
Qualifications
The ideal candidate should possess a minimum of three years of professional experience in software engineering. Proficiency in at least one programming language such as C# is essential, along with a solid understanding of Git, Docker, and software pipeline setup. Candidates should be comfortable navigating complex codebases, running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is advantageous. Strong problem-solving skills, attention to detail, and the ability to work independently are critical. Prior experience with LLM research, evaluation projects, or developer tools development will be considered a plus.
Responsibilities
- Analyze and triage GitHub issues across trending open-source libraries to identify challenging tasks for LLMs.
- Set up and configure code repositories, including environment setup and Dockerization, to facilitate testing and evaluation.
- Evaluate the quality and coverage of unit tests within repositories to ensure comprehensive testing frameworks.
- Modify and run codebases locally to assess the performance of LLMs in bug-fixing and code understanding scenarios.
- Collaborate closely with research teams to design and select repositories and issues that pose meaningful challenges for AI models.
- Lead and mentor junior engineers, fostering a collaborative environment and ensuring project milestones are met efficiently.
Benefits
Joining Turing provides the opportunity to work remotely in a flexible and fully distributed environment. You will be part of a pioneering team working on some of the most advanced AI projects in the industry, gaining exposure to cutting-edge research and development. Turing offers competitive compensation aligned with your experience and contributions. You will have access to continuous learning opportunities, professional growth, and the chance to collaborate with leading experts in AI and software engineering. Additionally, this role allows you to make a tangible impact on the future of AI-assisted programming and software development tools.
Equal Opportunity
Turing is an equal opportunity employer committed to fostering an inclusive environment for all employees. We celebrate diversity and are dedicated to creating a workplace where everyone feels valued and empowered to contribute their best. We do not discriminate based on race, ethnicity, gender, age, sexual orientation, disability, or any other protected characteristic. Our hiring practices are designed to ensure fairness and equal opportunity for all applicants.
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