Software Engineer, Personalization, Gemini App, Google DeepMind

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DeepMind seeks a Software Engineer, Personalization for the Gemini App to own end-to-end personalization features across the Gemini App stack and its models, collaborating with researchers, engineers and cross-functional partners. You’ll define metrics, evaluation standards, and acceptance criteria, and drive improvements from hypothesis to production in fine-tunable and frozen model contexts. Ideal candidates have Python, Colab, and C++ skills, a CS degree, and production ML experience with large language models and user-facing features. Extra advantages include LLM modeling and evaluation, collaboration with research teams, and a track record turning product vision into shipped features. Tip: tailor your resume with measurable impact, experiments, and cross-functional delivery, note onsite Zurich readiness, and the March 31 2026 deadline.

Snapshot

Make Gemini App the most personal assistant. Build personalization-related user-facing features spanning both the Gemini App stack and the Gemini models behind it. Identify quality gaps and issues, and take end-to-end ownership over the improvements. Work closely with research scientists, other software engineers, and cross-functional partners.

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

Join the Gemini App Personalization team in order to make Gemini App the most personal assistant. Gemini App is Google’s flagship LLM product, where you'll contribute to building cutting-edge personalization features on top of state-of-the-art Gemini models. Personalization is a top priority for the Gemini App, as we aim to:

• Build and launch new Gemini App personalization features and capabilities across all surfaces and powering all other Gemini App features and components.
• Expand or develop new personalization-related capabilities (e.g. understanding relevant personal information and using it appropriately in model responses and tool invocations) spanning both the Gemini App stack and the state-of-the-art Gemini models that are powering it.

Personalization features and capabilities are reaching hundreds of millions of users and are frequently highlighted by leads in high visibility external events (e.g. Google I/O, Made by Google).

Key responsibilities:

• Act as primary owner and critical judge for specific Personalization features/areas. You will define the key metrics, evaluation standards, and acceptance criteria that guide development.
• Own the end-to-end lifecycle of complex quality or infrastructure improvements from hypothesis and experimentation to production deployment across both fine-tunable and frozen model architectures.
• Propose and take end-to-end ownership over targeted quality or infrastructure improvements.
• Partner closely with research scientists, engineers and cross-functional partners (product and program managers) to advance the business goals of the organization.
• Influence and align with senior stakeholders and cross-functional leaders (Product, Research, Program Management) to shape the multi-quarter Personalization strategy and maximize organizational impact.

About You

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

• Proficiency in Python / Google Colab / C++
• Bachelor's degree in Computer Science or a related technical field
• Experience working with Machine Learning models (preferably Large Language Models) in a production environment
• Strong problem-solving and analytical skills, with the ability to design and execute complex experiments
• Experience building and shipping features for large-scale, user-facing products.

In addition, the following would be an advantage: 

• Experience with large language models Modeling and Evaluation (System instructions optimization, Context engineering, Eval design, Supervised Fine-Tuning, …)
• Experience with large language models Modeling for improving Personalization capabilities
• Experience in a role requiring close collaboration with research or applied science teams
• A proven ability to navigate ambiguity and translate high-level product vision into a concrete technical roadmap and shipped features.

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.

Application deadline: 12pm CET, 31st March 2026 

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.