Job Description
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience in software development (e.g., C++, Python).
- 2 years of experience in testing, maintaining, or launching software products.
- Experience building, training, and deploying machine learning models using TensorFlow, JAX, or Adbrain.
- Experience working with ranking, retrieval and other recommendation systems models.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures and algorithms.
- Experience with generative AI techniques (e.g., LLMs, natural language processing) and integrating them into production systems.
- Proven track record of managing large-scale ML systems, conducting analysis of quality systems, and identifying bottlenecks to improve performance.
- Excellent investigative and quantitative reasoning skills, with a foundation in statistics and experiment design (A/B testing).
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 an ML Engineer on the Travel Ads team, you will be at the forefront of integrating highly relevant travel ads into AI Overviews/AI Mode and web search experiences. You will bridge the gap between generative AI and core ads infrastructure. You will build and optimize the deep learning models powering ads ranking and retrieval alongside integrating LLMs.
You will leverage user intent and contextual signals to deliver ads that feel like a natural, helpful extension of the user's travel planning journey. This is a unique opportunity to apply your expertise in recommendation/search system and deep learning technology (Adbrain, TensorFlow, JAX) to scale features, drive significant business impact, and shape the future of travel discovery.
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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $147000 - $211000 (USD) + 15% bonus target + bonus + equity + benefitsLearn more about benefits at Google.Responsibilities
- Build, train, and scale deep learning models for ranking, retrieval and generation use cases using Adbrain, TensorFlow, or JAX, alongside efficient GenAI inference integration.
- Own the end-to-end design implementation, and deployment of robust ML features and data pipelines across AI surfaces, ensuring high code quality and system performance.
- Design, launch, and analyze A/B experiments to evaluate model performance, monitor user engagement, and drive improvements in ad relevance and business.
- Work closely with immediate teammates and cross-functional partners (Product, Data Science, UX) to clarify requirements and resolve technical blockers.
Numbers & Facts
| Location | Mountain View, CA |
| Industry | Computer Software |
| Company Size | 10,000 employees or more |
| Year Founded | 1998 |
| Website | https://goo.gle/4dbno6V |
Benefits
Paid Sick Days, Performance Bonus, Professional Development, 401K, Stock Options, Employee Events, Retirement / Pension Plans, Tuition Reimbursement, Work From Home, Life Insurance, On Site Cafeteria
About Company
Build for everyone
Since our founding in 1998, Google has grown by leaps and bounds. Starting from two computer science students in a university dorm room, we now have thousands of employees and offices around the world. These Googlers build products that help create opportunities for everyone, whether down the street or across the globe.
It starts with how we work together. We’re building a company where people of different views, backgrounds and experiences can do their best work and show up for one another. A place where every Googler feels like they belong.
So whether you develop new technology or creative campaigns, craft beautiful products or breakthrough partnerships, your work here is a chance to accomplish things that matter. Bring your insight, imagination, and healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.
Benefits
We strive to provide Googlers and their loved ones with a world-class benefits experience, focused on supporting their physical, financial, and emotional wellbeing. Our benefits are based on data, and centered around our users: Googlers and their families. They’re thoughtfully designed to enhance your health and wellbeing, and generous enough to make it easy for you to take good care of yourself (now, and in the future). So we can build for everyone, together.
Learn more about Google’s benefits on this site featuring Googlers’ experience.
How we Hire
Google’s hiring process is an important part of our culture. Googlers care deeply about their teams and the people who make them up. In order to build for everyone, we know that we need a wide range of perspectives and experiences, and a fair hiring process is the first step in getting there.
Skills
- A/B Testingunmatched
- Advertisingunmatched
- Algorithmsunmatched
- Analysis Skillsunmatched
- Artificial Intelligence (AI)unmatched
- Artificial Intelligence (AI) Natural Languageunmatched
- Business Growthunmatched
- C++ Programming Languageunmatched
- Computer Scienceunmatched
- Cross-Functionalunmatched
- Data Managementunmatched
- Data Scienceunmatched
- Data Storageunmatched
- Data Structuresunmatched
- Deep Learningunmatched
- Distributed Computingunmatched
- Equal Employment Opportunity (EEO)unmatched
- Experiment Designunmatched
- Information Retrievalunmatched
- Information/Data Security (InfoSec)unmatched
- Internet Searchunmatched
- JAX (Java API for XML)unmatched
- Large-Scale Systemsunmatched
- Leadershipunmatched
- Machine Learningunmatched
- Natural Language Processing (NLP)unmatched
- Network Designunmatched
- Performance Analysisunmatched
- Performance Managementunmatched
- Performance Modelingunmatched
- Process Improvementunmatched
- Product/Service Launchunmatched
- Production Systemsunmatched
- Python Programming/Scripting Languageunmatched
- Quantitative Analysisunmatched
- Small Businessunmatched
- Software Developmentunmatched
- Software Engineeringunmatched
- Statisticsunmatched
- Systems Analysisunmatched
- Travel Planningunmatched
- Use Casesunmatched
- User Interface Designunmatched
- User Interface/Experience (UI/UX)unmatched
- YouTubeunmatched
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