About The Position

Turing is hiring a Software Engineering evaluator to create datasets for training, benchmarking, and advancing large language models in collaboration with researchers. The work includes curating code examples, providing solutions, and correcting code primarily in Java, as well as Python, JavaScript (including ReactJS), C/C++, Rust, and Go. The evaluator will assess and refine AI-generated code for efficiency, scalability, and reliability, and work with cross-functional teams to improve enterprise-level AI-driven coding solutions. The role also involves building agents to verify code quality and identify error patterns; evaluating model capabilities across stages of the software engineering cycle, from prototyping and architecture/API design through production implementation, launch, experimentation, monitoring, and operational maintenance; and designing mechanisms to automatically verify solutions to software engineering tasks. This is a flexible contractor engagement requiring a minimum of 10 hours per week and up to 40 hours per week. The initial duration is one month, with potential extensions based on performance and fit. Candidates must be based in the US, Canada, or Western Europe countries listed in the posting. The application takes 15–30 minutes and requires completion of an AI video interview.

Requirements

  • At least 3 years of software engineering experience.
  • Strong expertise building full-stack applications and deploying scalable, production-grade software using modern languages and tools.
  • Deep understanding of software architecture, design, development, debugging, and code quality and review assessment.
  • Excellent oral and written communication skills for providing clear, structured evaluation rationales.
  • Must be based in the US, Canada, or a Western European country.

Responsibilities

  • Curate code examples, build solutions, and correct code for AI model training initiatives, primarily in Java and also in Python, JavaScript (including ReactJS), C/C++, Rust, and Go.
  • Evaluate and refine AI-generated code for efficiency, scalability, and reliability.
  • Collaborate with cross-functional teams to improve AI-driven coding solutions against industry performance benchmarks.
  • Build agents that verify code quality and identify error patterns.
  • Hypothesize about software engineering cycle steps and evaluate model capabilities across those steps.
  • Design verification mechanisms that can automatically verify solutions to software engineering tasks.
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