Job Description

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 one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

• 2 years of experience with data structures and algorithms.
• Experience in healthcare research.
• Experience in generative AI evaluations.
• Experience developing accessible technologies.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, you will join Google Health AI, an impact-driven research team whose mission is to catalyze the adoption of human-centered AI in healthcare and medicine. You will treat AI as transformational in these fields and a necessary component in realizing personalized medicine, expanding access for populations, improving quality and consistency, deploying care at the edge, and closing the loop of a learning healthcare system. Rather than addressing these objectives alone, you will partner with Google Product teams, Bets, external companies, non-profits, and governments to assess, develop, and deploy AI-powered breakthrough solutions that redefine the relationship between technology and health.

Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.

The US base salary range for this full-time position is $147,000-$211,000 + 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

• Collaborate with onsite clinicians, product managers, and other research/engineering teams in Google to influence the research and product direction of the teams.
• Develop and improve our AI models and multi-agent systems on testing tasks in health and wellness.
• Build and improve our AI research infrastructure (e.g., ingest new datasets from our clinical partners or real world users, collect high quality labels, set up quality control, training and evaluation infrastructure etc.).
• Address open-ended health research, with potential to publish externally.
• Build benchmarks for urgency triaging and diagnostics while integrating personal health information into care management activities.