Staff Engineer, Search Intelligence
Skills
- Java
- Kotlin
- C++
- Python
- Machine Learning
- Generative AI
- LLM
- System Design
- ML Infrastructure
- Reinforcement Learning
- Ranking
- Model Deployment
About the role
Responsibilities:
Be passionate about the Artificial Intelligence (AI) for personalization space and have prior knowledge working in this area and solve problems with increased levels of ambiguity. Have AI Fluency and be prepared to discuss your knowledge of AI tools in the hiring process.
Lead the architectural evolution of personalization across Google Search.
Work with Java, Kotlin, C++, Python (for model validation and Colabs).
Work with Magi Response Server (MaRS), Superroot, QFlow, GWS plugins, Magit/Silfra Orchestration.
Work on Gemini (e.g., 3.0 Pro, 3.0 Flash, V2S), Orbit/Nemo triggering classifiers, Sian (first-party (1P) integrations), Anima (Search activity), Footprints (privacy-safe, ephemeral storage), and online autoraters, EAS, SAIL, Sherlog.
Minimum qualifications:
Bachelor’s degree or equivalent practical experience.
5 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 Machine Learning (ML) field.
5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
5 years of experience testing, and launching software products.
3 years of experience with software design and architecture.
Experience integrating generative AI tools or Large Language Model (LLM) interfaces into workflows.
Preferred qualifications:
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
8 years of experience with data structures and algorithms.
5 years of experience testing, and launching software products. 3 years of experience with software design and architecture.
Experience with building or leveraging agentic frameworks and Large Language Model (LLM)-powered automation to enhance investigative velocity. Experience with building classifiers, machine learning, AI, ranking, and research.
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