Staff ML Engineer: Auto-Bidding for Search Ads

Google; Ionia (NY); On-site; USD 207,000 - 300,000; Full time

Job summary

Google is seeking a Staff ML Engineer for the Search Ads Auto-Bidding team in New York, NY. You will develop and deploy advanced ML models that optimize advertiser bids and ROI at scale. The role requires deep learning expertise, experience with transformers/LLMs, and proficiency in Python or C++.

You'll collaborate across teams to push production ML systems from research to deployment. You'll engage in design reviews, run experiments, monitor model health, and participate in on-call rotations

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of software development experience.
• 5 years testing and launching software, plus 3 years design/architecture experience.
• Experience with deep learning, transformers, or LLMs.
• Proficiency in Python or C++.

Responsibilities

• Innovate and iterate on machine learning model design to improve quality, stability, and efficiency across the 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.

Skills

Deep learning

Transformers/LLMs

Python

C++

ML model training and inference

Software architecture

Software testing and product launches

Education

Bachelor's degree or equivalent practical experience

Tools

TensorFlow

Keras

TFX

Job description

Google is seeking a Staff ML Engineer for the Search Ads Auto-Bidding team in New York, NY. You will develop and deploy advanced ML models that optimize advertiser bids and ROI at scale. The role requires deep learning expertise, experience with transformers/LLMs, and proficiency in Python or C++.

You'll collaborate across teams to push production ML systems from research to deployment. You'll engage in design reviews, run experiments, monitor model health, and participate in on-call rotations