Frontier Safety Mitigations Research Engineer, DeepMind

Google LLC; Greater London; Presencial; GBP 110.000 - 160.000; Jornada completa

Descripción de la vacante

DeepMind, London, UK, is seeking a Research Engineer to advance frontier safety mitigations in AI systems. You will design classifiers and data pipelines, build monitoring across contexts, and implement response mechanisms against persistent threats while integrating safety into the research-to-deployment lifecycle.

You will collaborate with software engineers and researchers to push automated red-teaming, threat modeling, and robust defenses in scalable production environments.

Formación

• Bachelor's degree in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
• 5 years of experience in software development, including experience with Python.
• Experience with the research-to-deployment pipeline in a frontier AI environment.
• Experience working in a software engineering or research team.

Responsabilidades

• Build advanced classifiers and data pipelines to detect misuse, and own the end-to-end process from automated evaluation to rapid model iteration.
• Build cross-context monitoring systems to detect coordinated harms, developing novel signal aggregation methods across disparate user sessions to identify large-scale attack vectors.
• Implement data-driven, semi-automated account-level response systems to detect, track, and apply strikes against persistent malicious actors using rich signals from production traffic.
• Evaluate and secure agentic AI systems by developing threat models, creating testing environments, and deploying robust mitigations against frontier-level agentic hacking and long-horizon attacks.
• Advance research in automated red-teaming and adversarial robustness, leveraging multi-turn/agentic attacks to systematically test for and uncover misuse vulnerabilities.

Conocimientos

Python

Research-to-deploy pipeline

Teamwork

Frontier AI

Cybersecurity

LLM training

TPUs

JAX

Adversarial ML

AI safety

Educación

Bachelor's degree in Computer Science / ML or related field

Herramientas

TPUs

JAX

Descripción del empleo

Frontier Safety Mitigations Research Engineer, DeepMind

DeepMind London, UK

• Bachelor's degree in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
• 5 years of experience in software development, including experience with Python.
• Experience with the research-to-deployment pipeline in a frontier AI environment.
• Experience working in a software engineering or research team.

Preferred qualifications:

• Experience with cybersecurity detection and response, building classifiers and anomaly detection systems at scale, taking safety defenses or mitigations from research concepts to scalable production systems.
• Experience collaborating on or leading applied ML projects, including LLM training, inference, and fine-tuning.
• Experience using AI coding agents with strong architectural judgement, and with TPUs and JAX.
• Background in adversarial machine learning, automated red-teaming, or model interpretability and probes.
• Knowledge of AI control, chain-of-thought monitoring, faithfulness, monitorability, and related frontier safety research.

About the job

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.

Responsibilities

• Build advanced classifiers and data pipelines to detect misuse, and own the end-to-end process from automated evaluation to rapid model iteration.
• Build cross-context monitoring systems to detect coordinated harms, developing novel signal aggregation methods across disparate user sessions to identify large-scale attack vectors.
• Implement data-driven, semi-automated account-level response systems to detect, track, and apply strikes against persistent malicious actors using rich signals from production traffic.
• Evaluate and secure agentic AI systems by developing threat models, creating testing environments, and deploying robust mitigations against frontier-level agentic hacking and long-horizon attacks.
• Advance research in automated red-teaming and adversarial robustness, leveraging multi-turn/agentic attacks to systematically test for and uncover misuse vulnerabilities.

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 .

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