Remote C# Developer

Turing
•Remote

About The Position

As a Software Engineering evaluator, you will 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 C/C++, as well as in Python, JavaScript (including ReactJS), Java, Rust, and Go. You will evaluate and refine AI-generated code for efficiency, scalability, and reliability, and work with cross-functional teams to improve enterprise-level AI-driven coding solutions. You will also build agents to verify code quality and identify error patterns, hypothesize about steps across the software engineering cycle, evaluate model capabilities at those steps, and design mechanisms that 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 specified Western European countries. The application process takes 15–30 minutes and requires an AI video interview.

Requirements

  • At least 3 years of software engineering experience.
  • Strong expertise in 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.
  • Candidates 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.
  • 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 them.
  • Design mechanisms to automatically verify solutions to software engineering tasks.
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