Staff ML Engineer, Search Ads Auto-Bidding

About the role

MINIMUM QUALIFICATIONS:

• Bachelor’s degree or equivalent practical experience.

• 8 years of experience in software development.

• 5 years of experience testing, and launching software products, and 3 years

of experience with software design and architecture.

• Experience with deep learning, transformers, or large language models (LLMs).
• Experience with machine learning model training and inference performance,

and programming in Python or C++.

PREFERRED QUALIFICATIONS:

• Master’s degree or PhD in Engineering, Computer Science, or a related

technical field.

• Experience designing and analyzing experiments for machine learning models.
• Experience with machine learning frameworks and libraries (e.g., TensorFlow,

Keras, or TFX).

• Experience deploying and maintaining machine learning systems in production

environments.

• Experience working with advertising systems or related 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.

The Search Ads Auto-Bidding team builds and maintains machine learning models

using AI and ML techniques to predict user interactions on Search Ads. These

models are a key component in setting advertisers' bids, with the goal of

improving both satisfaction and ROI for Search Ads advertisers using

auto-bidding products. By optimizing towards advertisers' objectives,

auto-bidding products drive Google's global Ads business, which serves users and

generates business growth.

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: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

• Innovate and iterate on machine learning model design to improve quality,

stability, and efficiency across the entire model lifecycle from concept to

deployment.

• Solve complex machine learning problems by designing, running, and analyzing

experiments using analytical and statistical methods.

• Contribute to code health, automation, and alerting systems to ensure model

stability and performance.

• Participate in on-call rotations for model health and collaborate with team

members to support critical systems.