Senior Software Engineer, Applied AI

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.

The Automotive AI team is a part of a bigger applied AI organization that builds conversational agents deployed at a large-scale that achieve very meaningful results in the real world.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s 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.

Work on Gemini enterprise for customer experience solutions.

Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).

Build AI vehicle integration with Gemini’s reasoning into our automotive products.

Work closely with the business stakeholders as well as other Engineering teams at Google such as DeepMind.

Build various AI/ML technologies, Large Language Models (LLMs) and Natural Language Understanding (NLU) infrastructure.

Minimum qualifications:

Bachelor’s degree or equivalent practical experience.

5 years of experience with software development in one or more programming languages.

3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.

Preferred qualifications:

Master's degree or PhD in Computer Science, or a related technical field.

5 years of experience with data structures and algorithms.

1 year of experience in a technical leadership role.

Experience developing accessible technologies.