Software Engineer, LLM, Search Ads
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience programming in Python or C++.
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 3 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.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:
- Master's degree or PhD in Computer Science or a related technical field.
- 5 years of experience with data structures and algorithms.
- 1 year of experience in a technical leadership role.
- Experience developing accessible technologies.
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.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
AdsML develops experimentation paths for large embedding models (LEM) and large language models (LLM) for Ads use cases. The Techniques and Toolkits team is responsible for making innovative modeling techniques available in the AdBrain platform for training machine learning models. This involves a range of activities from prototyping and experimenting with new modeling techniques that push the cost-quality boundary, as well as adapting the model authoring framework to productionize these techniques and make them widely available.
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 $166,000-$244,000 + 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
- Work across many different aspects of machine learning development and infrastructure.
- Collaborate with our modeling team partners to explore new modeling and analysis techniques to accelerate LEM and LLM development.
- Engage with users and infrastructure developers to understand requirements, pain points, and new use cases.
- Investigate and implement efficient ways to support training of new modeling techniques on large-scale ML training platforms.
- Design and implement new capabilities in training infrastructure. Investigate issues with training speed, throughput, blockers, etc., and be familiar with implications on serving.
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If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
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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