Senior ML Safety Engineer - Ads Platform

Google; Southwestern Ontario; On-site; CAD 182,000 - 186,000; Full time

Job summary

Google is seeking software engineers to strengthen the Ads Safety Enablement and Prevention team. You will build scalable, intelligent systems to stop bad actors and help legitimate advertisers.

You will collaborate across Ads, Trust & Safety, GBO, and DeepMind to apply modern ML techniques and create explainable clustering solutions. The role requires strong software development experience, ML capability, and a track record in architecture and testing.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 2 years of experience with one or more of the following languages: SQL, R, Python, or C++.
• 2 years of experience building Machine Learning (ML) solutions.

Responsibilities

• Develop innovative solutions to classify and understand actors and their assets including destinations in Google Ads using modern machine learning techniques.
• Collaborate with partner teams to provide holistic solutions to detect and stop bad actors from re-entering Google Ads, and to reduce friction for good actors.
• Build effective and explainable clustering-based solutions to ensure consistent treatment of both good and bad actors in Google Ads.

Skills

Software development

SQL

Python

C++

Machine Learning

Software design

Testing

Education

Bachelor's degree or equivalent practical experience

Job description

Google is seeking software engineers to strengthen the Ads Safety Enablement and Prevention team. You will build scalable, intelligent systems to stop bad actors and help legitimate advertisers.

You will collaborate across Ads, Trust & Safety, GBO, and DeepMind to apply modern ML techniques and create explainable clustering solutions. The role requires strong software development experience, ML capability, and a track record in architecture and testing.