Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Research, experiment and prototype novel approaches for analyzing model behavior and failure patterns.
Conduct targeted empirical investigations into model outputs, agent trajectories, and error patterns to inform benchmark design and improve evaluation trustworthiness.
Implement, test, and refine benchmark suites evaluating complex agentic reasoning across code, math, and specialized domains, ensuring high discriminability and zero data contamination.
Develop and maintain pipelines that transform benchmark/sandbox execution logs, agent traces, and runtime artifacts into high-fidelity evaluation datasets and training data.
Partner closely with research scientists, senior engineers, and cross-functional teams to translate research insights into practical evaluation infrastructure.
Minimum qualifications
Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
1 year of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
Experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling, computer vision).
Experience in Generative AI.
Experience in Python.
Preferred qualifications
Master's degree or PhD in Computer Science or related technical fields.
2 years of experience with data structures and algorithms.
Experience developing accessible technologies.
Skills and experience in data analysis.
Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
1 year of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
Experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling, computer vision).
Experience in Generative AI.
Experience in Python.