Research Engineer, Cyber Gemini, DeepMind

Google DeepMind

New York (NY)

On-site

USD 174,000 - 252,000

Full time

33 hours ago
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Job summary

Google DeepMind is seeking a research-focused Software Engineer to advance Gemini Cyber and CodeMender, applying ML and cybersecurity know-how to build scalable, secure AI systems.

You will work at the intersection of research and engineering, contributing to large-scale experiments, datasets, and evaluation platforms while collaborating across teams to push frontier capabilities in AI safety and defense.

Qualifications

  • Bachelor's degree in Computer Science, or a related technical field, or equivalent practical experience.
  • At least 5 years of experience with large language models (LLMs), including pre-training or fine-tuning.
  • Preferred: experience with cybersecurity, data processing pipelines, and leading research collaborations.

Responsibilities

  • Contribute to Gemini Cyber by building training recipes and cybersecurity datasets, benchmarks, and evaluation platforms for vulnerability finding and fixing.
  • Build datasets (RL environments, SFT data) and iterate on post-training recipes.
  • Integrate novel ML techniques into research prototypes and scalable infrastructure.
  • Build evaluation pipelines and leaderboards to rigorously measure agent performance.
  • Optimize system performance, latency, and resource utilization for serving large models.

Skills

LLM experience
Applied research leadership
Cybersecurity awareness

Education

Bachelor's degree in Computer Science or related field

Job 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: New York, NY, USA; Mountain View, CA, USA; San Francisco, CA, USA.

Minimum qualifications
  • Bachelor's degree in Computer Science, or a related technical field, or equivalent practical experience.
  • 5 years of experience with large language models (LLM), including pre-training or fine-tuning.
Preferred qualifications
  • Experience with Cyber Security (in particular, application security and vulnerability research).
  • Experience with running large-scale data processing pipelines.
  • Experience collaborating on or leading applied research projects.
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. AI’s cyberattack capability is increasing rapidly and it is becoming important to address the emerging challenges for Code Security. To address this, we recently announced and released Gemini Flash 3.5 Cyber and CodeMender. A capable cybersecurity model, combined with a sophisticated harness enables defenders to find and fix high severity vulnerabilities before malicious actors do. In this role, you will work at the intersection of research and engineering to advance the capabilities of Gemini and CodeMender in autonomous vulnerability discovery and fixing. Together, you will apply ML and cybersecurity knowledge to make software more secure, building both research prototypes and robust, scalable infrastructure. 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
  • Contribute to Gemini Cyber, collaborating across organizations to build high-quality training recipes, cybersecurity datasets, benchmarks, and evaluation platforms for vulnerability finding and fixing.
  • Build datasets (RL environments, SFT data) and iterate on post-training recipes.
  • Integrate novel ML and agentic techniques into research prototypes.
  • Build evaluation pipelines, benchmarks, and leaderboards to rigorously measure agent performance.
  • Optimize system performance, latency, and resource utilization for serving large models.

Learn more about benefits at Google .

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 .

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