Senior Staff Software Engineer, AI/ML GenAI, Google Ads
Job Summary
Job Description
- 8+ years software development experience
- 5+ years GenAI experience (LLMs, Multi-Modal)
- 7+ years leading technical projects, ML design
- Experience with large-scale ML infrastructure
- Design, develop, test, deploy, maintain software
- Master's or PhD in related field
- Experience in a complex, matrixed organization
- Technical leadership experience leading teams
- Bonus
- Equity
- Benefits
9 skills required
Job Details
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience with design and architecture; and testing/launching software products.
- 5 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
- 7 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures/algorithms.
- 5 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.
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.
Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
The US base salary range for this full-time position is $248,000-$349,000 + 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 .
Responsibilities
- Design, develop, test, deploy, maintain, and enhance large scale software solutions.
- Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.
- Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.
- Drive technical project strategy, lead large-scale ML infrastructure optimization, and oversee the design and implementation of state-of-the-art GenAI solutions.
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