Senior Software Engineer, AI​/ML, Security

Senior Staff Software Engineer, AI/ML, Security

Google, Kirkland, WA, USA;
Seattle, WA, USA; +1 more

Benefits for this role include:

• Health, dental, vision, life, disability insurance
• Retirement Benefits: 401(k) with company match
• Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
• Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
• Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year

Note:

By applying to this position you will have an opportunity to share your preferred working location from the following:
Kirkland, WA, USA;
Seattle, WA, USA;
Sunnyvale, CA, USA
.

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 7 years of experience leading technical project strategy, ML design, and working with industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 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 with design and architecture; and testing/launching software products.
• 5 years of experience in Cloud.

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 8 years of experience with data structures and algorithms.
• 5 years of experience in a technical leadership role leading project teams and setting technical direction.
• 5 years of programming experience in Java.
• Experience with AI model security, adversarial machine learning, or data privacy (e.g., prompt injection defenses, LLM introspection).
• Experience delivering enterprise-grade security products that achieve measurable, high-impact business and customer outcomes.

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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 Senior Staff Software Engineer for AI/ML Security, you will serve as the primary technical visionary for Model Armor and Sensitive Data Protection, supporting the strategy to secure LLMs against prompt injection, jail breaking, and data exfiltration. You will manage deep architectural issues by integrating filter-based defenses into scalable, observable, and explainable distributed systems that protect enterprise customers at Google Cloud scale.

Beyond technical execution, you will navigate extreme ambiguity to drive overarching business strategy and lead high-stakes, cross-Google initiatives. You will have a master-level ability to negotiate and forge consensus among elite researchers and engineers, translating security goals into measurable, high-impact solutions for the generative AI era.

The US base salary range for this full-time position is $262,000-$365,000 plus bonus, equity, and 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…