About The Position

Turing is seeking 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 precise solutions, and correcting code, primarily in Rust, as well as Python, JavaScript (including ReactJS), C/C++, Java, and Go. The evaluator will assess and refine AI-generated code for efficiency, scalability, and reliability, and collaborate 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, including prototyping, architecture and API design, production implementation, launch, experiments, monitoring, and operational maintenance; and designing mechanisms that can automatically verify solutions to software engineering tasks. This is a contractor engagement lasting one month, with potential extensions based on performance and fit. The flexible commitment is at least 10 hours per week and up to 40 hours per week. Candidates must be based in the US, Canada, or the specified Western European countries: Austria, Belgium, France, or Germany. The engagement does not include medical benefits or paid leave. Applicants must complete 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 clear, structured evaluation rationales.
  • Must be based in the US, Canada, or Austria, Belgium, France, or Germany.
  • Must complete an AI video interview.

Responsibilities

  • Curate code examples, provide precise solutions, and correct code for AI model training initiatives, primarily in Rust and also in Python, JavaScript (including ReactJS), C/C++, Java, 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.
  • Evaluate model capabilities across software engineering stages, including prototyping, architecture design, API design, production implementation, launch, experiments, monitoring, and operational maintenance.
  • Design verification mechanisms that can automatically verify solutions to software engineering tasks.
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