Staff Software Engineer Lead, AI/ML
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products.
- 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 ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 3 years of experience with software design and architecture.
Preferred qualifications:
- Master's or PhD degree in Computer Science or related field such as Math, Physics or Engineering with emphasis on Machine Learning.
- 6 years of work experience, or 3 years of work experience with a PhD in Computer Science or related technical field.
- Experience with modern Machine Learning techniques including deep learning, transformers, and model optimization.
- Experience building and deploying large-scale machine learning models, for recommendation applications.
- Excellent communication skills with the ability to collaborate effectively across teams and functions.
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.
The Google Display Ads (GDA) machine learning (ML) team is at the forefront of revolutionizing digital advertising through machine learning. We develop the core intelligence that powers Google's display ads, building sophisticated models, signal representations, and systems for retrieval, ranking, and pricing. Our work is an essential component behind optimized bidding and automation, directly impacting the open and free internet. We leverage techniques, including the latest advancements in Large Language Models (LLMs), to train and deploy models at massive scale. Processing billions of training samples daily, utilizing hundreds of thousands of CPUs and TPUs, we manage some of the most challenging optimization problems in the industry.
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 $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
- Define the long-term technical roadmap and lead the design of complex, high-performance model architectures, embeddings, and componentization for optimizing prediction quality and scale.
- Pioneer the integration of AI/ML advancements to deliver step-change improvements in model performance and system efficiency.
- Architect and advocate the development of advanced personalization and real-time retrieval systems to enhance ad relevance and user experience.
- Own the optimization strategy for training and serving, maximizing the utilization of dedicated TPU/GPU clusters and writing high-performance production code (e.g., C++) as necessary.
- Provide strong technical guidance and mentorship to junior and mid-level engineers, leading large, cross-functional projects, and elevating the team's engineering excellence.
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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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