Software Engineer III, AI/ML, Ads Auction Models
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.
Discover Ads owns the Ad Auction along with a bulk of the ML models that go into predicting various auction components. To run an Ad Auction efficiently, we need to predict many different user actions accurately (e.g., click-through-rate, likelihood of a conversion, user satisfaction with the ads, and many others.
In this role, you will be an expert in ML and data analysis. You will join a high-velocity modeling team that owns the core ML models for Auction ranking and pricing. Our work directly impacts user experience and advertiser ROI through state-of-the-art personalization. You will leverage Google’s most advanced ML infrastructure to build large-scale deep neural networks.
We collaborate with Google DeepMind (GDM) and Ads AI to push the boundaries in recommendation systems.
The US base salary range for this full-time position is $141,000-$202,000 + 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
- Build end-to-end machine learning systems on large-scale data.
- Research novel ideas on model architectures and analysis, and then build, experiment and deploy them.
- Analyse data and feature engineering.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience programming in Python or C++.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- 1 year of experience with one or more of the following: Recommendation System, reinforcement learning (e.g., sequential decision making) or specialization in another ML field.
- Experience with data analysis and SQL.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures or algorithms.
- Experience developing accessible technologies.
- Experience with auction theory or game theory.