Job Type
Job Details
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 3 years of experience with Machine Learning (ML) infrastructure (e.g., model deployment, model evaluation, data processing, debugging).
Preferred qualifications:
- Experience in complex technical projects, from conception to deployment, with a focus on delivering results on time.
- Experience in a research or academic setting, collaborating with researchers and translating research findings into practical applications.
- Experience in machine learning, deep learning, and AI development, with a track record of building and deploying production-level models.
- Experience in Partner and devices product portfolio and an understanding of AI.
- Ability to work effectively with diverse and distributed teams, including product managers, researchers, and other stakeholders, across multiple time zones to drive AI adoption and integration.
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.
- Develop, train, evaluate, and deploy AI/ML models, ensuring their robustness, scalability, and successful integration into production systems.
- Collaborate with Partners and Devices Forum (P&D) product teams and research teams to deliver AI-based features.
- Work with the team, leveraging their proximity and partnerships with product teams to maximize efficiency and impact.
- Identify common needs across multiple engagements and build shared infra and models which will serve as a common toolset and blueprints to deliver the next engagements faster.
- Transfer valuable AI knowledge and expertise to the product teams you engage with, empowering them for future AI-driven initiatives.
