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DeepMind

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Research Engineer, Machine Learning, GeminiApp Personalization, DeepMind

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Summary

Research engineer on Google DeepMind's Gemini App team building personalized AI-assistant features across the full Gemini stack: analyzing user feedback and logs, improving personalization quality via fine-tuning or prompting, and developing automated and human-in-the-loop evaluations. Core tech: Python or C++, ML, LLMs, and applied AI.

We are the Gemini App team in DeepMind, building the next-generation AI assistant from Google. Be at the forefront of AI innovation with Gemini, featuring native multimodality, an expansive context window (up to 2 million tokens), and performance. Our mission is to empower billions of people by providing deeply personalised and helpful products. In this role, you will be a part of a team building a personal AI assistant that is tailored to the unique interests, passions, and curiosities of individuals.

Artificial intelligence will be one of humanity’s most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
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.
  • Design, prototype, and build robust, scalable, user-facing personalization features on the full Gemini App stack.
  • Perform relevant data analysis of user feedback, logs, and evaluation tasks to identify personalization-related quality issues and opportunities.
  • Propose and implement targeted quality improvements via fine-tuning or prompting.
  • Develop evaluation techniques (both automated and with a human in the loop) to assess a hill-climb on personalization quality.
  • Contribute to the development of a data flywheel, driving continuous improvement and innovation.

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience with software development in one or more programming languages.
  • 5 years of experience programming in Python or C++.
  • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  • 2 years of experience with Machine Learning, Large Language Models (LLMs), or applied AI.
  • 2 years of work or educational experience in machine learning and deep learning.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical fields.
  • 1 year of experience in a technical leadership role.
  • Experience developing accessible technologies.

Skills

See also

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