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Deepmind Jobs in California (NOW HIRING)

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Deepmind information

What is a DeepMind job?

A DeepMind job refers to a role within DeepMind, an artificial intelligence research company owned by Alphabet. DeepMind hires experts in AI, machine learning, neuroscience, and related fields to work on advanced research and real-world applications of AI. Positions range from research scientists and engineers to ethics and policy specialists. Employees contribute to cutting-edge projects in healthcare, robotics, and general AI development.

What are the typical daily responsibilities for someone working at DeepMind?

Professionals at DeepMind generally focus on developing and testing novel AI algorithms, conducting cutting-edge research, and publishing findings in academic conferences or journals. Daily tasks may include collaborating with other researchers and engineers, designing experiments, analyzing large datasets, and participating in team meetings to discuss research directions. Teamwork is central, as projects often require input from experts in multiple disciplines such as neuroscience, engineering, and mathematics. This collaborative environment enables innovative breakthroughs and fosters continuous learning and growth.

What are the key skills and qualifications needed to thrive in the DeepMind position, and why are they important?

To thrive at DeepMind, strong expertise in machine learning, artificial intelligence research, and advanced mathematics is typically required, backed by a degree in computer science or a related field, often at the PhD level. Familiarity with coding languages such as Python or C++, and experience with deep learning frameworks like TensorFlow or PyTorch, is essential. Collaboration, creativity, and complex problem-solving are crucial soft skills for working within multidisciplinary research teams. These abilities enable impactful research, innovative solutions, and effective teamwork in a rapidly evolving AI landscape.

How do I get a job at DeepMind?

To apply for a job at DeepMind, visit their careers website to browse current openings and submit an application online. Candidates typically need a strong background in machine learning, artificial intelligence, or related fields, along with relevant experience or research contributions. Preparing a tailored resume and demonstrating technical skills can improve your chances of being considered.

What cities in California are hiring for Deepmind jobs?

Cities in California with the most Deepmind job openings:

Infographic showing various Deepmind job openings in California as of August 2026, with employment types broken down into 1% Internship, 97% Full Time, 1% Part Time, and 1% Contract. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution.

Senior Product Manager, Gemini Post-Training, DeepMind

DeepMind

Mountain View, CA โ€ข On-site

$149K - $197K/yr

Full-time

Re-posted 2 days ago


Job description

Minimum qualifications:
  • Bachelor's degree in a technical field, or equivalent practical experience.
  • 8 years of experience in product management, with a focus on AI/ML, data systems, or agentic frameworks.

Preferred qualifications:
  • Proven experience in managing large-scale data pipelines, dataset curation, or environment generation for machine learning.
  • Demonstrated ability to lead cross-functional teams, shape research culture, and manage complex stakeholder relationships in highly ambiguous environments.

About the job
At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.
In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.
One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.
In this role, you will orchestrate a massive domain expansion, integrating Reinforcement Learning (RL) environments across professional verticals (e.g., science, healthcare, broader enterprise). Your work will directly address core capabilities such as long-trajectory actions (hours-long tasks), multi-step tool use on real-world APIs, and automatic context management. You will also work on translating these wins to first- and third-party harnesses to land these capabilities to millions of users.
Artificial intelligence will be one of humanity's most transformative inventions. At Google 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: $256000 - $278000 (USD) 20% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities
  • Oversee the generation and integration of data across many expert domains targeting production-level quality for hours-long agentic tasks. Define key user journeys and relevant task distributions on the basis of User Experience Research (UXR), user interviews, and engaged industry analyses.
  • Work closely with modeling teams to carefully measure and improve model generalization to real Application Programming Interface (APIs).
  • Design new internal post-training evaluations for the most critical areas, demonstrating Gemini quality across world knowledge, tool use, and context engineering.

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