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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