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Research Software Engineer

Google DeepMind • LLM & Generative AI • Foundation Models • Bachelor's Degree • 1 day ago

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Salary

≈ $158k – $292k per year (Estimated)

Location

In office (Cambridge)

Seniority

Senior · 5+ years exp

Confirmed on the employer's own hiring board on Sep 30, 2026. First seen by Alion on Sep 29, 2026.

Overview

Company

Impact

Profile match

Google DeepMind

Google DeepMind is the artificial intelligence research and engineering division of Alphabet, formed in 2023 by merging the London laboratory founded in 2010 with the Google Brain team. It builds frontier foundation models such as the Gemini family, generative media systems including Veo and Imagen, and scientific tools like AlphaFold, whose protein structure predictions earned a share of the 2024 Nobel Prize in Chemistry. The unit pairs long-horizon research on reinforcement learning and general intelligence with product delivery across Google Search, Workspace, Android and Google Cloud.

deepmind.google • HQ: London, United Kingdom • LLM & Generative AI • AI for Science • Foundation Models • AI Research Labs • 1001-5000 employees • Est. 2010

Tech stack of Google DeepMind

About the job

At Google DeepMind our mission is to build the world's first general-purpose learning agent. Central to this mission is the complex task of measuring the intelligence of our prototypes. As a Software Engineer, you will be working with the cutting edge AI agents developed by our exceptional team of Machine Learning and Neuroscience research scientists. Your responsibilities will include everything from creating systems for agent testing using 2D and 3D games to developing test problems within physics simulators. You will create graphical visualization of results, build competitive agent leaderboards and test new algorithms on robots. To succeed in this role you will need to have a strong foundation in software engineering and enjoy working on a wide range of challenging problems within a mission-driven team.

Help design and build innovative ways of working with AI systems. Collaborate with research scientists and engineers to advance the frontier of human-AI interaction and expand the capabilities of AI for users.

This role requires software engineering expertise combined with an applied understanding of machine learning and interface design.

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: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

Write product or system development code.
Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.

Qualifications

Minimum qualifications:

Bachelor’s degree or equivalent practical experience.
5 years of industry experience with 2 years in machine learning or software engineering.
2 years of experience with software development in one or more programming languages.

Preferred qualifications:

Master's degree or PhD in Computer Science or related technical fields.
Experience developing accessible technologies.

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