Research Engineer, Agentic Security for Gemini, DeepMind
Google DeepMindSan Francisco, California, USposted 16h ago
EMPLOYMENT
Full-time
COMPENSATION
$174k - 252k/yr
ARRANGEMENT
On-site
At a glance
Build post-training data, adversarial evaluations, and guardrails that improve Gemini’s security and privacy across agentic capabilities while preserving model utility.
Summarized by AI from the original posting
What you'll do
- Build post-training data and tools to improve Gemini's security and privacy capabilities
- Integrate improvements into current versions of Gemini
- Coordinate with stakeholders on Gemini tool use, coding, and agentic capabilities
- Improve adversarial evaluation and auto-red teaming techniques
- Develop out-of-model guardrails
- Generalize solutions into reusable libraries and frameworks for protecting agents and models
- Share knowledge through publications, open source, and education
Requirements
- 011 year of experience training or fine-tuning generative models
- 02Experience in machine learning safety, security, privacy, or alignment
- 03Experience with JAX, PyTorch, or a similar machine learning framework
- 04Strong Python skills demonstrated through readable, scalable, reusable ML software
- 05Experience building readable and reusable ML software
Perks
15% bonus targetEquityBenefits
Skills
JAXPyTorchPythonMachine LearningGenerative ModelsMl SafetyMl SecurityMl PrivacyMl AlignmentPost TrainingAdversarial EvaluationAuto Red Teaming
Full description
Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; San Francisco, CA, USA.Minimum qualifications:
• Master's degree in Computer Science or related quantitative field.
• 1 year of experience in training or fine-tuning generative models to improve capabilities.
• Experience in one of the machine learning safety, security, privacy, or alignment fields.
• Experience in one machine learning framework such as JAX or PyTorch.
• Experience building readabl and reusable ML software.
Preferred qualifications:
• Experience with JAX, PyTorch, or similar machine learning platforms.
• Experience in Python through strong artifacts in building readable, scalable, reusable ML software.
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 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: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Responsibilities
Learn more about benefits at Google .
• Build post-training data and tools to improve Gemini's security & privacy capabilities across coding, personal assistant, and other agentic capabilities; integrating improvements into latest versions of Gemini.
• Coordinate closely with stakeholders working on Gemini's tool use, coding and other agentic capabilities to ensure security & privacy gains in the model do not impact Gemini's utility.
• Collaborate with other team members to improve our adversarial evaluation (auto-red teaming) techniques and out-of-model guardrails.
• Amplify the impact by generalizing solutions into reusable libraries and frameworks for protecting agents and models across Google, and by sharing knowledge through publications, open source, and education.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .