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 Web Health team's mission is to build user trust by ensuring Google shows a helpful mix of websites across all Search traffic. We achieve this by owning the full ML lifecycle, from developing state-of-the-art models to deploying them directly across Web Ranking and GenAI surfaces.
We are looking for an ML engineer with a deep care for and understanding of the intricate interplay between data, algorithms, objectives and business impact.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
- Own projects end-to-end from initial idea to design, analysis, and implementation.
- Collect, analyze and visualize data from various sources to formulate and test hypotheses.
- Design and implement ML systems from training data composition to hyperparameter tuning to post-deployment monitoring and optimizations.
- Understand and build upon latest technologies such as Gemini foundational models using distillation and fine-tuning.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in C++ or Python.
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 3 years of experience specializing in a machine learning field (e.g., foundational models, ML infrastructure, reinforcement learning, or similar areas).
- 3 years of experience with end-to-end machine learning (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:
- PhD (or industry research experience) in ML, AI or related technical fields.
- Experience in full-cycle development and productionization of machine learning systems.
- Experience in distilling and deploying production-grade LLMs.
- Experience programming in Kotlin.