Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience testing, and launching software products.
- Experience in adversarial testing, red teaming, GenAI/AI safety, GenAI/AI ethics or responsibility, or similar.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures/algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.
- Experience in AI/ML security research, including areas like adversarial machine learning, prompt injection, model extraction, or privacy-preserving ML.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a Staff Software Engineer for Adversarial ML, you'll apply an attacker mindset and adversarial machine learning expertise to simulate threat actor attacks on Google's ML-based products. Your work will focus on identifying the potential impact of these attacks on Google products and users, and enhancing our resilience against them. You'll also be responsible for testing and improving our ability to detect these specific classes of attacks. A key aspect of this role involves raising awareness of adversarial threats to ML deployments—spanning security, abuse, and privacy—and drawing attention to their business impact.
The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Develop and expand the machine learning (ML) red team program and its overall impact.
- Plan, lead, and execute realistic ML red team exercises, stepping into the role of an attacker targeting ML deployments in our products.
- Design and build tools and infrastructure to support ML red team exercises.
- Document and present exercise results to diverse audiences, from technical engineers to non-technical subject matter experts and senior leadership.
- Collaborate closely with product teams to help them identify and implement mitigations against successful attacks on ML deployments.