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Open nowFirst seen 4 hours ago

Software Engineer, App Ads Bidding and Optimization

Google3,180 open roles

Where
Mountain View, CA, USA
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Your applicationOpen nowSoftware Engineer, App Ads Bidding and OptimizationGoogle · Mountain View, CA, USA

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Google's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 29 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: first seen 4 hours ago

Google median: 29 days open

The posting

In most instances, this position requires in-person interviews as part of the hiring process.

Minimum qualifications:

  • Bachelor's degree in Computer Science or related technical field or equivalent practical experience.
  • 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
  • Experience in software development using C++.
  • Experience in conducting quantitative data analysis, statistical modeling, and interpreting datasets.
  • Experience in mathematical optimization, and statistical learning.

Preferred qualifications:

  • Experience in system design, including defining technical architecture, system interfaces, and data models.
  • Experience in programming languages used for data analysis and computational statistics (e.g., Python, R, MATLAB, C++, Java, or Go).
  • Experience with Colab, SQL, and other data analysis tools.
  • Experience working with one or more of the following: distributed and parallel systems, machine learning models, information retrieval, and mathematical optimization techniques including linear programming, convex optimization, or reinforcement learning.
  • Strong quantitative reasoning skills, demonstrated in a mathematical field such as data science, optimization, machine learning, or natural science.

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 at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.

Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Improve the accuracy and stability of the UAC bidder with statistical analysis and new ML/optimization algorithms. Improve/modernize bidding infrastructure and design and implement bidding algorithms for faster cold start for new campaigns.
  • Debug inaccuracies in bidding infrastructure and suggest improvements and launch with design, implementation, experimentation and analysis.
  • Incorporate and engineer input features from ad creatives, publisher pages/content, as well as users’ personalized ad history to improve bidding and modeling accuracy.
  • Improve the efficiency and reliability of ML models by designing novel model architectures and adopting robust development and release processes. Debug and troubleshoot complex interactions between business goals, mathematical models, and infrastructure.
  • Work with PM, UX, and partners teams to design and deliver new ad experiences. Leverage data and metrics to help evaluate product success and drive business decisions.
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