Senior Product Solutions Engineer, GenAI Robotics, gTech
Google creates products and services that make the world a better place, and gTech’s role is to help bring them to life. Our teams of trusted advisors support customers globally. Our solutions are rooted in our technical skill, product expertise, and a thorough understanding of our customers’ complex needs. Whether the answer is a bespoke solution to solve a unique problem, or a new tool that can scale across Google, everything we do aims to ensure our customers benefit from the full potential of Google products.
To learn more about gTech, check out our video.
US: $152000 - $221000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
- Conduct 1:1 technical consultation and brainstorming sessions with partners to guide them in developing innovative solutions using Google's Gemini ER, Gemini VLA, and Gemini/Gemma LLM models.
- Provide expert technical guidance on API integration, model customization (where applicable), prompt engineering, and solution architecture for Robotics projects.
- Create simulations for robotics models in AI Studio, as well as create demos to showcase robotics models' capabilities.
- Gather, synthesize, and relay partner feedback, use cases, and technical requirements to internal Google product and engineering teams to influence future development.
- Collaborate closely with Product Managers/Engineers and Global Partnerships teams to ensure a cohesive and supportive experience for partners.
Minimum qualifications:
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 6 years of experience working with client-side web technologies (e.g., HTML, CSS, JavaScript, or HTTP).
- 6 years of experience coding with one or more programming languages (e.g., Java, C/C++, Python).
- Experience troubleshooting technical issues for internal/external partners or customers.
Preferred qualifications:
- Master’s degree in Engineering, Computer Science, Business, or a related field.
- Experience in an investigative role such as business intelligence, data analytics, or statistics.
- Experience working with database technologies (e.g., SQL, NoSQL).
- Experience with cloud technologies such as architecting, developing, or maintaining cloud solutions in virtualized environments or cloud data engineering.
- Experience using Machine Learning and building solutions.
- Experience working with systems (e.g., Linux, Unix, Windows).