You will design, develop, and maintain robust CI/CD pipelines to automate the deployment of our lowside and highside products. You will collaborate closely with product and engineering teams to enhance existing application code for improved compatibility and streamlined integration within automated pipelines.

Contribute to the overall architecture and design of our deployment systems, bringing new ideas to life for increased efficiency and reliability. Troubleshoot and resolve complex deployment issues, ensuring minimal disruption to development cycles.

Develop a deep understanding of our product and ML architectures to facilitate seamless integration and deployment. Document pipeline processes and configurations to ensure maintainability and knowledge transfer.

Proactively incorporate security best practices into all stages of the CI/CD pipeline, building security into our development processes. Drive standardization and foster collaboration across different product teams to achieve a unified and efficient SDLC.

We are looking for experienced DevOps Engineers, DevSecOps Engineers, Software Engineers with a strong focus on CI/CD, or a similar role. You should have a proven track record of building or significantly enhancing CI/CD pipelines.

Experience configuring and adapting application code to integrate seamlessly with evolving CI/CD environments is a plus. Familiarity with standard containerization & deployment technologies like Kubernetes, Terraform, Docker, etc. is also required.

We offer a competitive salary range of $245,600-$307,000 USD, comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. This role may be eligible for additional benefits such as a commuter stipend.

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In this role, you will design and execute test strategies for our applications, APIs and machine learning models. Your work will involve automated testing, edge-case analysis, and collaboration with cross-functional teams to deliver seamless, high-quality user experiences.

Key responsibilities include:

• Test Automation: Develop automated test suites to validate app features, APIs, and model integrations, ensuring end-to-end reliability and user experience. • Edge Case Analysis: Collaborate with PMs and other stakeholders to identify and rigorously test edge cases, improving the robustness of both platform features and models. • Quality Platform Development: Contribute to building tools and frameworks that enable more efficient and scalable quality testing processes across the organization. • Release Readiness Validation: Implement pre-release quality gates to validate models, APIs, and platform updates, providing a green light for production releases. • Systematic QA Campaigns: Design and lead comprehensive quality assurance campaigns, including functional, stress, and performance testing, to proactively identify potential issues.

About you:

• You have proven ability to create and execute comprehensive test strategies, covering functional, regression, and exploratory testing for AI products. • You are proficient in QA tools like Playwright, Postman, or similar platforms for API and functional testing. • You’re skilled in identifying, documenting, and collaborating with developers to resolve issues efficiently. • You are autonomous and a self-starter. • You are a proactive problem-solver with a continuous improvement mindset. • You are proficient in Python or Typescript.

Now it would be ideal if you have:

• Experience testing Machine Learning models. • Understanding of the Machine Learning lifecycle. • Experience in various types of testing: performance, load, accessibility or others. • Strong debugging skills.

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As a Chemist in the Responsible Development & Innovation (ReDI) team at Google DeepMind, you will be a principal architect of the safety protocols governing the intersection of Large Language Models (LLMs) and the chemical sciences. You will design and execute rigorous safety evaluations and inform mitigation strategies that ensure our frontier models accelerate scientific discovery without compromising global security.

This role is pivotal in deciding when and how our most advanced AI systems are released to the world.

You will apply your knowledge of chemistry to devise evaluation methodologies (e.g. red-teaming, knowledge elicitation studies, etc.) and contribute to building and running these evaluations on new models. You will analyse the results from evaluations, communicate them clearly to advise and inform decision-makers on the safety of our AI systems, and use them to refine our harm frameworks and inform our mitigation strategies.

In this role, you will work closely with other Subject-Matter Experts (SMEs) in the chemical, biological, radiological and nuclear domains, Research Engineers and Research Scientists focused on developing AI systems, as well as experts in AI ethics and policy.

Key Responsibilities:

• Architect of Safety Evaluations: Build rigorous, scalable frameworks to evaluate model proficiency in overcoming key bottlenecks in CWA precursor acquisition, chemical synthesis, and weaponisation.
• Strategic Advisory: Analyse evaluation results to brief executive decision-makers on model safety, directly influencing deployment 'Go/No-Go' decisions.
• Harm Framework Innovation: Refine our internal safety taxonomies to account for emergent risks at the intersection of general AI and specialist models like AlphaFold.
• Collaborative Mitigation: Partner with Research Engineers to revise mitigation strategies and refine harm frameworks for identified chemical risks. Work with other SMEs in the chemical, biological, radiological, nuclear, and conventional explosive domains to build a unified defence against CBRNE-related risks.
• External Engagement: Stay abreast of global chemical security trends and international non-proliferation policy through engagement with external international, governmental, and non-governmental organisations.

About You:

You are a seasoned scientist who bridges the gap between laboratory chemistry and emerging technology. You are motivated by the challenge of defending complex systems and possess the critical mindset required to anticipate non-obvious misuse scenarios.

Minimum Qualifications:

• Chemistry Expertise: PhD in synthetic organic chemistry with at least two years post-doctoral or equivalent experience.
• Publication Record: Proven experience publishing as a first author in high-impact general science or chemistry-specific journals, and presenting work at international chemistry conferences. Classified or internal reporting experience will be considered in lieu of public records for candidates from roles in national security.
• Security Domain Expertise: Comprehensive understanding of the Chemical Weapons Convention (CWC) and other national and international CWA agreements/treaties, chemical defence protocols, and the landscape of dual-use research in the chemical domain.
• Systems Thinking: The ability to translate high-level chemical risks into technical requirements for AI safety.
• Communication Excellence: A proven ability in distilling complex technical findings into clear, actionable advice for non-specialist stakeholders.

Preferred Experience:

• Knowledge of CWA defence, including synthesis, detection, and countermeasures.
• Direct experience with CBRNE mitigation, non-proliferation, or relevant international security stakeholders.
• Familiarity with the machine learning lifecycle and AI Safety Frameworks.
• Experience using and/or developing computational chemistry tools (e.g., AlphaFold, retrosynthesis engines, etc.).
• Working knowledge of the Frontier Safety Framework (FSF), Critical Capability Levels (CCLs), and similar documents published by other leading AI labs.
• Understanding of Google DeepMind AI research output (e.g., AlphaFold, GNoME, WeatherNext, etc.), and AI products (e.g., Gemini, Nano Banana, Genie, etc.).
• Passion for the ethical deployment of frontier technologies and AI policy.

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