Research Engineer, Gemini Personalization

Sorry, this job was removed at 06:04 p.m. (CST) on Tuesday, Apr 22, 2025
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2 Locations
In-Office
Artificial Intelligence
The Role

Snapshot:

We are the Gemini App team in Google DeepMind, building the everyday 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 superior performance. Our mission is to empower billions with deeply personalised and helpful products, delivering an experience users love.

In this role you will be a part of a team building a personal AI assistant. One that doesn’t just answer general questions, but understands you — tailoring its help to your specific interests, passions, and curiosities.

About Us:

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The Role:

As a Research Engineer, you'll play a key role in building the state-of-the-art personalized AI assistant on Gemini. Our personalization research encompasses model innovation, post-training refinement, advanced evaluation, benchmark creation, data generation, and scalable deployment.

This includes improving the model’s ability to reason about user information, creating robust evaluation frameworks to measure personalization quality, and building scalable systems to deliver tailored experiences to a wide user base. A key aspect of the work involves continuous experimentation and refinement to push the boundaries of what a truly personal AI assistant can achieve.

About You:

We seek out individuals who thrive in ambiguity and who are willing to help out with whatever moves prototypes forward. We regularly need to invent novel solutions to problems, and often change course if our ideas don’t work out, so flexibility and adaptability to work on any project is a must.

In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

  • BSc, MSc or PhD/DPhil degree in computer science, mathematics, applied stats, machine learning or similar experience working in industry
  • Proven knowledge and experience of Python or C++
  • Deep understanding of machine learning and statistics 
  • Strong knowledge of algorithm design and data structures
  • Proven experience with TensorFlow, JAX, PyTorch, or similar leading deep learning frameworks
  • Recent experience conducting applied research to improve the quality and training/serving efficiency of large transformer-based models
  • Experience fine-tuning and adaptation of LLMs (e.g. supervised fine-tuning, RLHF)
  • Experience applying and productionizing state-of-the-art large visual, language and multimodal research into real-world applications
  • Experience with user modeling techniques tailored for personalization
  • Understanding of personalization metrics and evaluation challenges (e.g., relevance, diversity, novelty, serendipity, offline vs. online evaluation)
  • Solid understanding of Deep Learning fundamentals, including transformer architectures, attention mechanisms, and optimization techniques
  • Software Engineering experience and experience working on large-scale ML projects highly desirable 
  • Experience with data pipelines and techniques for managing, processing, and utilizing large-scale user data while adhering to privacy best practices
  • Ability to design and analyze rigorous offline and online (A/B) experiments to validate personalization improvements
  • Proven experience working in industry, working on projects from proof-of-concept through to implementation highly beneficial.
  • A passion for Artificial Intelligence
  • Excellent communication skills and proven interpersonal skills, with a track record of effective collaboration with cross-functional teams

In addition, the following would be an advantage:

  • Experience in applying experimental ideas to applied problems
  • Cross functional collaboration experience
  • Prior experience collaborating with researchers
  • Prior experience working with product teams

The US base salary range for this full-time position is between $166,000 - $244,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Application deadline: 12pm PST Friday 9th May 2025 

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

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The Company
1,218 Employees
Year Founded: 2010

What We Do

We’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI).

Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges.

We have a track record of breakthroughs in fundamental AI research, published in journals like Nature, Science, and more.Our programs have learned to diagnose eye diseases as effectively as the world’s top doctors, to save 30% of the energy used to keep data centres cool, and to predict the complex 3D shapes of proteins - which could one day transform how drugs are invented.

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