Research Engineer, Responsible Frontier AI Research, DeepMind

Google LLC; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

Google DeepMind in London invites applications for a Share Research Engineer, Responsible Frontier AI Research. The role focuses on AI safety and responsible research, building scalable systems and evaluating model safety across releases.

Ideal candidates have advanced degrees and hands-on Python/C++ experience, with a track record in ML safety and evaluation frameworks. You will work across teams to advance responsible AI innovations at Google DeepMind.

Qualifications

• Master's degree or PhD in Computer Science or a related technical field.
• Experience working on AI safety or responsible AI research.

Responsibilities

• Prototype and deliver scalable engineering solutions across the Responsibility research portfolio.
• Architect and optimize training and inference pipelines to detect and evaluate harmful manipulation behaviors in frontier language models.
• Develop post-training strategies to mitigate manipulation risks including deceptive persuasion, sycophancy, and covert influence tactics.
• Collaborate with Research Scientists to translate safety research into robust implementations and present results to cross-functional stakeholders.
• Build and maintain evaluation infrastructure to systematically track model safety performance across releases.

Skills

AI safety

Responsible AI research

Evaluation frameworks

Pipelines for ML models

Education

Master's degree or PhD in Computer Science or related

Focus on Machine Learning

Tools

Python

C++

Job description

Share Research Engineer, Responsible Frontier AI Research, DeepMind

corporate_fare DeepMind place London, UK

• Master's degree or PhD in Computer Science or a related technical field.


• Experience working on AI safety or responsible AI research.

Preferred qualifications:

• Master's degree or PhD in Computer Science, Engineering, or a related field with a focus on Machine Learning.


• Experience in Python and C++ for high-performance ML library development.


• Experience with Large Language Model (LLM) demitigation, adverserial robustness, harmful manipulation detection, or AI safety evaluation and mitigation.


• Experience building evaluation frameworks, benchmarks, or automated testing pipelines for ML models.


• Prior experience working directly on AI safety, or responsible AI research.

About the job

At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers. 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 varied learning opportunities and career pathways for those driven to achieve exceptional results through collective effort.

Responsibilities

• Prototype and deliver scalable engineering solutions across the Responsibility research portfolio.


• Architect and optimize training and inference pipelines to detect and evaluate harmful manipulation behaviors in frontier language models.


• Develop post-training strategies to mitigate manipulation risks including deceptive persuasion, sycophancy, and covert influence tactics.


• Collaborate with Research Scientists to translate safety research into robust implementations and present results to cross-functional stakeholders.


• Build and maintain evaluation infrastructure to systematically track model safety performance across releases.

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 .

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.

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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.