Research Software Engineer, Generative AI Evaluations, Health AI

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 2 years of experience with data structures or algorithms.
• Experience in AI/ML research and Generative AI agent development.
• One or more scientific publication submission(s) for conferences (eg, CVPR/ECCV/ICCV/NeurIPS/ICLR), journals, or public repositories
  

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, a technical related field, or equivalent practical experience.
• 4 years of experience in AI/ML research or agent development.
• Experience leading evaluation efforts for complex AI systems, particularly AI agents or interactive AI.
• Understanding of current AI agent architectures (e.g., LLM-based agents, reinforcement learning agents) and their evaluation issues.
• Familiarity with the unique tests of evaluating AI in health-related applications, such as safety, need for clinical validation, etc.
• Excellent programming skills with Python.

About the job

At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.

Our mission is to help people in understanding and improving their health. Our team works towards this goal by developing innovative solutions like a personal health agent and new sensing and intelligence features for health and home across Google surfaces.

Google for Health is a company-wide effort to help billions of people be healthier. We work toward this vision by meeting people in their everyday moments and empowering them to stay healthy and partnering with care teams to provide more accurate and accessible care. Our teams are applying our expertise and technology to improve health outcomes globally – with high-quality information and tools to help people manage their health and wellbeing, solutions to transform care delivery, research to catalyze the use of artificial intelligence for the screening and diagnosis of disease, and data and insights to the public health community.

The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Ensure robust and iterative evaluation of health features, establishing methods for continuous monitoring, feedback loops, and adaptation to new data or clinical insights.
• Collaborate with cross-functional teams (e.g., Research, Engineering, Product, Clinical, Legal, Ethics) to define evaluation requirements, interpret results, and drive improvements in AI models and health applications.
• Conduct in-depth analysis of AI agent behavior, identify failure modes, and provide actionable insights to improve model performance and safety.
• Stay at the forefront of research in AI evaluation, particularly in areas of agent-based systems, human-AI interaction, and the specific issues of evaluating AI in consumer health and wellness.
• Develop and advocate best practices, tools, and documentation for AI agent evaluation across health-related projects.