About The Company
Turing is a leading technology company dedicated to advancing artificial intelligence and machine learning solutions. Renowned for its innovative approach, Turing specializes in developing cutting-edge AI systems that transform industries and empower businesses worldwide. With a strong focus on research and development, the company fosters an environment of collaboration, creativity, and continuous learning. Turing's commitment to excellence and its mission to accelerate the deployment of powerful AI technologies make it a sought-after employer for top-tier talent in the tech industry. As a pioneer in AI-driven solutions, Turing strives to push the boundaries of what is possible, ensuring its clients stay ahead in a rapidly evolving digital landscape.
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 is pivotal in building datasets that enable LLMs to effectively address realistic software engineering challenges. The ideal candidate will possess a deep understanding of high-quality public repositories on GitHub and have the ability to contribute significantly to our project efforts. Responsibilities include automating development environments, triaging issues, and assessing test coverage and code quality. This position offers a unique opportunity to work at the intersection of software engineering and AI research, contributing to projects that shape the future of AI-assisted software development.
Qualifications
The ideal candidate should have a minimum of three years of professional experience in software engineering, with a strong background in JavaScript and TypeScript. Proficiency with version control systems like Git, containerization tools such as Docker, and experience setting up and managing software pipelines are essential. Candidates should demonstrate the ability to understand and navigate complex codebases, run, modify, and test real-world projects locally. Prior experience contributing to or evaluating open-source projects is highly desirable. Additional skills include familiarity with automation tools, experience in AI or LLM research is a plus, and excellent problem-solving abilities are required to succeed in this role.
Responsibilities
- Analyze and triage issues across trending open-source repositories on GitHub, identifying areas for improvement and testing.
- Set up, configure, and optimize code repositories, including Dockerization and environment management.
- Evaluate unit test coverage and quality to ensure robustness and reliability of codebases.
- 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 challenging repositories and issues that effectively test LLM capabilities.
- Lead and mentor junior engineers, fostering a collaborative environment and ensuring high-quality project deliverables.
Benefits
Joining Turing provides the opportunity to work remotely in a flexible environment, enabling a healthy work-life balance. You will be engaged in cutting-edge AI projects alongside industry-leading experts, offering continuous learning and professional growth. Turing values innovation and recognizes talent, providing competitive compensation for contractors. The company also supports a dynamic work culture that encourages creativity, collaboration, and the pursuit of excellence. Additionally, working on projects that influence the future of AI and software engineering provides a fulfilling and impactful career experience.
Equal Opportunity
Turing is committed to creating an inclusive and diverse workplace. We are an equal opportunity employer and welcome applications from individuals of all backgrounds, regardless of race, gender, age, religion, sexual orientation, or disability. We believe that diversity fosters innovation and drives success, and we strive to ensure all employees feel valued and empowered. Our hiring practices are designed to promote fairness and equal opportunity for all candidates.
