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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Add predictive modeling of the interests and creators a user will engage with next. Train with multi-objective goals (engagement, satisfaction).
Redesign the interest vocabulary for much higher precision, and evaluate learned alternatives to today's interest vocab.
Build deep, sequence-based token models that learn from long user activity histories across Google products.
Build offline evaluation that predicts online results (profile-quality autoraters, retrieval and ranking metrics), and run well-sliced live experiments.
Design a shared token description, feature set, and training objectives across token types.
Minimum qualifications
Bachelor’s degree or equivalent practical experience.
5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), Recommender Systems, deep learning, or personalization.
3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
3 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production, and experience building architecture.
Experience with deep learning architectures and related algorithms (e.g., Transformers).
Preferred qualifications
Master's degree or PhD in Computer Science or 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.
Bachelor’s degree or equivalent practical experience.
5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), Recommender Systems, deep learning, or personalization.
3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
3 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production, and experience building architecture.
Experience with deep learning architectures and related algorithms (e.g., Transformers).
