Job description

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 Discover Ads team aims to bring premium quality ads to Discover users, and it will make a huge impact on advertisers and Google. There is a big focus on improving Ads Quality and Personalization: finding the right products for the right users to create our Ads is crucial for our product success. Our team owns the core models which predict signals for our ranking system. Ranking an ad requires many predictions in different stages of ads serving stack. We build models to predict many different user actions accurately; e.g., click-through-rate, likelihood of a conversion, and others. In this role you will focus on solving quality challenges via state of the art ML algorithms and feature engineering techniques. 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 - $210000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google . • Write product or system development code. • 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 to improve prediction qualities. • Work with latest ML techniques, tools like TensorFlow, Adbrain, TPU, and Recommendation systems. • Bachelor’s degree 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. • 1 year of experience with end-to-end machine learning (e.g., model deployment, model evaluation, optimization, data processing, debugging). • 1 year of experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production. Minimum qualifications: • Bachelor’s degree 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. • 1 year of experience with end-to-end machine learning (e.g., model deployment, model evaluation, optimization, data processing, debugging). • 1 year of experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production. Preferred qualifications: • Master's degree or PhD in Computer Science or related technical fields. • 2 years of experience with data structures and algorithms. • Experience developing accessible technologies. • Experience with Ads.

Requirements

Must-haves

Ranking an ad requires many predictions in different stages of ads serving stack. We build models to predict many different user actions accurately; e.g., click-through-rate, likelihood of a conversion, and others.
In this role you will focus on solving quality challenges via state of the art ML algorithms and feature engineering techniques.
Learn more about benefits at Google .
Write product or system development code.
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 to improve prediction qualities.
Work with latest ML techniques, tools like TensorFlow, Adbrain, TPU, and Recommendation systems.
Bachelor’s degree 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.
1 year of experience with end-to-end machine learning (e.g., model deployment, model evaluation, optimization, data processing, debugging).
1 year of experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production.
Bachelor’s degree 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.
1 year of experience with end-to-end machine learning (e.g., model deployment, model evaluation, optimization, data processing, debugging).
1 year of experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production.
2 years of experience with data structures and algorithms.

Nice-to-haves

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Master's degree or PhD in Computer Science or related technical fields.
Experience developing accessible technologies.
Experience with Ads.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlmachine learning

Platform: google
Effort: medium