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.
Search Live is a voice-first conversational experience for AI Mode, which enables users to have a multi-turn audio-forward experience with Search.
In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
Responsibilities
- Run evaluations and document wins and losses.
- Research for solutions to address losses in a horizontal manner.
- Do model optimizations using several different techniques.
- Collaborate within the team and cross functionally to increase the team's impact.
- Refine and automate Mars deployment workflows using Kotlin.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 2 years 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.
- 2 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 3 years of experience with software design and architecture.
- Experience in AI, machine learning, or related technologies.