Software Engineer, AI/ML Data and Training Infrastructure

Google•Mountain View, CA

5d•Remote

About The Position

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 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.

Requirements

Bachelor's degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages, including Python and C++.
3 years of experience with ML Models and ML infrastructure (e.g., data processing, model optimization, evaluation, deployment).
2 years of experience with software design and architecture.

Nice To Haves

Experience iterating and managing projects.
Experience collaborating with and supporting multiple client teams.
Experience with large-scale distributed system design and research.
Understanding of ML systems and generative AI technology.

Responsibilities

Advance the platform to enable further ML use-case for discover feed recommendation.
Design, implement, deploy, and maintain various projects.
Take project ownership, including ideation, implementation, analysis, and maintenance.
Learn and apply the technique to transform the product.
Collaborate with peer team members (ranking, retrieval) for understanding various needs and system limitations in order to make informed decisions.