Senior Software Developer, Ads Safety Enablement and Prevention – Google – Waterloo, ON
At Google‘s Waterloo campus, the Ads Safety Enablement and Prevention team is on a mission to protect the integrity of one of the world’s most trusted digital advertising ecosystems. This Senior Software Developer role sits at the intersection of machine learning, large-scale system design, and real-world impact — helping safeguard billions of users while protecting over $250 billion in annual revenue.
Day-to-day, you’ll be building intelligent, scalable systems that stop bad actors before they reach users and reduce friction for legitimate advertisers. You’ll work alongside partner teams in Ads, Trust & Safety, GBO, and DeepMind, applying modern ML techniques to detect risk and establish trust as early in the process as possible.
About the Role: Senior Software Developer, Ads Safety
This position is embedded within the Ads Safety Enablement and Prevention team, which operates on the principle that prevention is the best cure. You’ll be developing innovative classification and clustering solutions to distinguish good actors from bad ones across the Google Ads ecosystem — building tools that are both effective and explainable. The work involves deep collaboration with cross-functional teams and a commitment to leveraging the latest in machine learning to stay ahead of emerging threats.
As a senior contributor, you’ll be expected to bring leadership qualities and versatility across the full stack. Google’s software developers are encouraged to grow, pivot across teams, and take on new challenges as the business evolves. English proficiency is required for this role, given the global nature of collaboration at Google.
Benefits and Salary
This role offers a competitive compensation package. The salary range in Canada is $182,000 – $186,000 CAD, plus a 15% bonus target, equity, and a comprehensive benefits package. Google’s benefits include a wide range of health, financial, and lifestyle supports — details are available on Google’s official benefits page.
Job Details
🏢 Company: Google
📍 Location: Waterloo, ON, Canada
📌 Job Type: Mid-level
💰 Pay: $182,000 – $186,000 CAD/year + 15% bonus target + equity + benefits
Responsibilities
In this role, you’ll be tackling some of the most technically complex challenges in digital advertising safety. Your work will directly shape how Google Ads identifies, classifies, and responds to bad actors — while keeping the experience smooth for legitimate advertisers. Here’s what the work looks like in practice:
- Develop innovative ML solutions to classify and understand actors and their assets, including ad destinations within Google Ads, using modern machine learning techniques
- Collaborate with partner teams across Ads, Trust & Safety, GBO, and DeepMind to deliver holistic solutions that prevent bad actors from re-entering the platform
- Reduce friction for good actors by building systems that can distinguish trustworthy advertisers and allow them to operate with minimal disruption
- Build clustering-based solutions that are both effective and explainable, ensuring consistent treatment across the full spectrum of actors in the ecosystem
- Contribute to system design and architecture as a senior developer bringing both technical depth and leadership to the team
Requirements / Skills
Google is looking for a seasoned software developer with hands-on experience in machine learning and a track record of building and shipping production-grade software. The ideal candidate is technically strong, comfortable with ambiguity, and excited about the challenge of protecting a platform used by billions of people worldwide.
- Bachelor’s degree or equivalent practical experience in a relevant technical field
- 5 years of software development experience in one or more programming languages
- 3 years of experience testing, maintaining, or launching software products, with at least 1 year focused on software design and architecture
- 2 years of experience with one or more of: SQL, R, Python, or C++
- 2 years of experience building ML solutions in a production or research context
- Preferred: Master’s degree or PhD in Computer Science or a related field
- Preferred: 5 years of experience with data structures and algorithms
- Preferred: 1 year in a technical leadership role and experience developing accessible technologies
How to Apply
To apply, visit the official Google Careers posting using the link below. Make sure your resume is up to date and tailored to highlight your machine learning and software development experience before submitting.
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Job Summary & Tips for Applying
Quick Summary & What to Highlight: This Senior Software Developer role at Google in Waterloo is perfect for candidates who excel in machine learning, large-scale system design, and software architecture. On your resume, emphasize any experience with ML model development, classification and clustering systems, and proficiency in languages like Python, SQL, or C++. If you’ve previously worked in ads technology, trust & safety, or applied ML, make sure to highlight specific achievements and responsibilities that align with this position.
Resume & Application Tips: Before applying, tailor your resume to match the job description. Include keywords like machine learning, software design and architecture, and Python or SQL that appear in the posting. Quantify your achievements where possible (e.g., “built ML pipeline processing 10M+ events daily” or “reduced false positive rate by 20% in ad classification system”). Write a brief cover letter expressing your genuine interest in Google‘s Ads Safety mission and why you’re excited about this opportunity in Waterloo. Double-check your application for spelling errors and ensure your contact information is current.
Interview Preparation: If selected for an interview, research Google‘s values, its approach to Ads Safety, and the broader Trust & Safety ecosystem beforehand. Prepare specific examples using the STAR method (Situation, Task, Action, Result) to demonstrate your ML development and cross-team collaboration skills. Common questions may include scenarios about system design at scale, handling ambiguous data problems, and balancing precision vs. recall in classification models. Dress appropriately for a technology environment, arrive 10–15 minutes early, and bring copies of your resume. Prepare thoughtful questions about the team’s current ML stack, how success is measured, and growth opportunities within Ads Safety. After the interview, send a thank-you email within 24 hours reiterating your interest in the position.