Senior Software Engineer – LLM Evaluation

New
J
JobgetherLLM evaluation
Must be based in the United States, Canada, or an eligible Western European country.ContractSenior
Salary not disclosed
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Job Details

Experience
3+ years of professional software-engineering experience.
Required Skills
PythonFull Stack DevelopmentJavaJavascriptSoftware ArchitectureC++ReactRust

Requirements

  • Have 3+ years of professional software-engineering experience.
  • Bring strong full-stack development capabilities and experience building scalable, production-grade software.
  • Have a strong understanding of software architecture, system design, API design, and production implementation.
  • Demonstrate knowledge of software development, debugging, code review, and code-quality assessment.
  • Be able to review, troubleshoot, and improve complex software implementations.
  • Be proficient in one or more relevant programming languages, such as Python, JavaScript, Java, C++, or Rust.
  • Have familiarity with software monitoring, operational maintenance, and production reliability.
  • Be able to evaluate technical decisions across the software-engineering lifecycle.
  • Bring analytical and problem-solving skills and a rigorous, detail-oriented approach to technical evaluation.
  • Be able to produce concise, well-structured evaluation rationales.
  • Be based in the United States, Canada, or an eligible Western European country.
  • Be willing to complete a required AI video interview.

Responsibilities

  • Curate code examples and technical datasets for model training, benchmarking, and evaluation.
  • Develop software-engineering solutions and improve implementations across multiple programming languages.
  • Evaluate AI-generated code for correctness, maintainability, efficiency, scalability, reliability, and engineering standards.
  • Identify implementation weaknesses, recurring coding errors, and patterns in AI-generated software.
  • Provide structured rationales for technical evaluation decisions and assessment outcomes.
  • Build agents and automated mechanisms to assess code quality and verify software solutions.
  • Design checks for consistent and reproducible evaluation across engineering tasks.
  • Evaluate AI capabilities across the software-development lifecycle, from architecture and prototyping through production and maintenance.
  • Collaborate with research and technical teams to define evaluation strategies and improve coding benchmarks.
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