About The Position

Turing is hiring a Java Developer as a Software Engineering evaluator to create datasets for training, benchmarking, and advancing large language models, working closely with researchers. The work involves 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 collaborate with cross-functional teams on 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, and designing mechanisms that can automatically verify solutions to software engineering tasks. This is a flexible contractor engagement requiring at least 10 hours per week and up to 40 hours per week. The stated duration is one month, with potential extensions based on performance and fit. Candidates must be based in the US, Canada, or specified Western European countries.

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 the listed Western European countries.

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 and evaluate model capabilities across software engineering stages, including prototyping, architecture design, API design, production implementation, launch, experiments, monitoring, and operational maintenance.
  • Design mechanisms that can automatically verify solutions to software engineering tasks.
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