Software Engineer for AI Model Evaluation

Lead the design and execution of evaluation frameworks, benchmarks, datasets, and tooling that measure and improve next-generation coding agents. This hands-on role combines AI research, software engineering, and model evaluation to define how frontier coding models are assessed and advanced.

• Design and own evaluation frameworks for coding agents, including benchmark specifications, scoring methodologies, rubrics, and quality standards.
• Lead end-to-end research initiatives to measure and improve coding model performance across diverse software engineering tasks.
• Develop high-quality datasets, golden examples, and evaluation protocols that enable reliable assessment of frontier coding systems.
• Analyze model behavior and failure modes, identify systematic weaknesses, and translate findings into actionable improvements for training and evaluation.
• Build tooling and infrastructure to support large-scale experimentation, data generation, review workflows, and evaluation pipelines.
• Establish best practices for coding-agent assessment, ensuring methodological rigor, reproducibility, and measurement quality.
• Partner with researchers, engineers, and applied AI teams to design experiments and evaluate emerging model capabilities.
• Contribute to technical reports, benchmark studies, and client-facing research deliverables that communicate model performance and insights.

• 3+ years of experience in software engineering, machine learning, AI research, evaluation, or related technical disciplines.
• Strong software engineering skills, proficient in Python, C++, or comparable programming languages.
• Experience designing, reviewing, or validating technical assessments, benchmarks, coding tasks, or evaluation methodologies.
• Familiarity with large language models, coding agents, reinforcement learning, model evaluation, or related AI systems.
• Proven ability to build tooling, automate workflows, and improve technical processes through systematic experimentation.
• Strong analytical skills, able to investigate model behavior and derive insights from complex systems.
• Excellent written and verbal communication skills, able to present technical findings to diverse audiences.
• Comfortable operating in fast-moving research environments with significant ambiguity and evolving priorities.
• Preferred, but not required: experience working on frontier AI systems, coding agents, or model evaluation research; track record of driving ambiguous research or technical projects end to end; experience designing benchmarks or datasets at scale; familiarity with agentic workflows, tool use, reinforcement learning, or post-training methodologies; publications, open-source contributions, or demonstrated technical leadership in AI.

Full-time position, fully remote. Role is part of the Coding Research core team and involves hands-on research and engineering work focused on coding agent evaluation.

Annual compensation range: $400, 000 to $800, 000 per year.