15 hours ago
London, United KingdomMid Level
Responsibilities
- Build a full-stack Universal Assistant prototype spanning agent infrastructure, multi-agent systems, and full-stack integration.
- Guide model inference, optimization, fine-tuning, and evaluation to improve system capabilities and reliability.
- Support synthetic data generation and prompt optimization workflows.
- Collaborate with DeepMind, Gemini, and Gemini App teams to integrate and evaluate agentic capabilities.
Requirements
- Bachelor's degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.
- At least 2 years of experience conducting research or engineering systems.
- At least 2 years of experience building in Python.
- At least 2 years of experience with agentic AI workflows, frameworks, and approaches.
- Preferred: Master's degree or PhD in Computer Science, Machine Learning, or a related field.
- Preferred: experience with data collection, model fine-tuning, evaluation, inference optimization, or extensive prompt tuning.
- Preferred: publication record at leading conferences on agentic AI and multimodal LLMs.
Tech Stack
Categories
AI Research
About Google
Google builds consumer and enterprise software and services including Search, Android, YouTube, Chrome, Maps, Gmail, and Google Cloud. Its business model centers on digital advertising and paid cloud, software, and hardware offerings (e.g., Pixel and Nest) for consumers, developers, and organizations. Founded in 1998 and headquartered in Mountain View, California, Google operates globally as a subsidiary of Alphabet Inc.