Research Engineer, Machine Learning, GeminiApp Personalization, DeepMind

Google; Town of Montana (WI); On-site; USD 174,000 - 252,000; Full time

Benefits offered by this job

Equity

Bonus

Benefits

Job summary

Google's Gemini App team in DeepMind is recruiting a Research Engineer (Machine Learning) to build personalized AI experiences within the Gemini App stack in Mountain View, CA. You will shape personalization features, analyze data, and drive quality improvements in a high-impact, fast-moving environment.

The role emphasizes deep ML/LLM work, software architecture, and collaboration across interdisciplinary teams, with equity and performance bonuses as part of the compensation.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5 years of software development experience.
• 5 years Python or C++ experience.
• 3 years testing/maintaining/launching software; 1 year design/architecture.
• 2 years ML/LLMs or applied AI experience.
• 2 years ML and deep learning experience.

Responsibilities

• Design, prototype, and build scalable personalization features on the Gemini App stack.
• Analyze user feedback, logs, and evaluation tasks to identify quality issues.
• Propose and implement improvements via fine-tuning or prompting.
• Develop evaluation techniques for personalization quality improvements.
• Contribute to data flywheel initiatives driving continuous innovation.

Skills

Python/C++

Software development

ML/LLMs

Testing/launching software

Architecture/design

Education

Bachelor's degree

Master's/PhD (preferred)

Job description

Research Engineer, Machine Learning, GeminiApp Personalization, DeepMind

Location: Mountain View, CA, USA

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.

About the job

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: $174,000 - $252,000 (USD) + 15% bonus target + equity + benefits

Responsibilities

• 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.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.