AI/ML Search Ads Engineer: ROI & Production ML

Google; Mountain View (CA); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

engineeringjobs.net, Inc. in Mountain View seeks an ML engineer to develop, train, and deploy large-scale models predicting user value and ad interactions to improve advertiser ROI in Search Ads.

You will analyze experiments, enhance model quality and efficiency, and collaborate with Research and Infrastructure teams on production ML systems; requirements include a Bachelor's degree or equivalent, 2+ years in Python or C++, and 1 year building recommender models.

Qualifications

• Bachelor's degree or equivalent practical experience required; 2+ years in software development (Python or C++).
• At least 1 year building and deploying recommendation models in production and 1 year of end-to-end ML experience.
• Master's or PhD and production ML systems experience with TensorFlow, Keras, or TFX preferred.

Responsibilities

• Develop, train, deploy, and maintain large-scale ML models for predicting user value and ad interactions.
• Analyze experiments to improve model quality, stability, and efficiency; automate and monitor pipelines.
• Collaborate with Research and Infrastructure teams to ensure robust, low-latency production ML systems.

Skills

Python

C++

Machine Learning

Recommendation Systems

Model Deployment

Model Evaluation

Statistical Analysis

Mathematical Modeling

Numerical Analysis

Experiment Design

TensorFlow

Keras

TFX

Search Ads Bidding

Low-Latency Coding

Return on Investment Optimization

Education

Bachelor's degree or equivalent practical experience

Master's degree or PhD (preferred)

Tools

TensorFlow

Keras

TFX

Google Ads

Job description

engineeringjobs.net, Inc. in Mountain View seeks an ML engineer to develop, train, and deploy large-scale models predicting user value and ad interactions to improve advertiser ROI in Search Ads.

You will analyze experiments, enhance model quality and efficiency, and collaborate with Research and Infrastructure teams on production ML systems; requirements include a Bachelor's degree or equivalent, 2+ years in Python or C++, and 1 year building recommender models.