Senior Software Developer, Machine Learning, Applied AI – Google – Toronto, ON
Location: Toronto, ON | Company: Google
If you’re a senior engineer with deep roots in machine learning and applied AI, Google is looking for someone like you to join their Cloud Applied AI (AAI) team — with the option to work out of Toronto, ON, Waterloo, ON, Sunnyvale, CA, or New York, NY. This is a mid-level role on one of the most ambitious AI product portfolios in the industry, powering next-generation conversational AI agents through the Gemini Enterprise ecosystem.
Day-to-day, you’ll be deeply involved in the full developer journey for AI Agents — from building and evaluating to optimizing, deploying, and monitoring. You’ll work at the intersection of ML infrastructure, agentic workflows, and real product impact, collaborating across a complex, cross-functional organization to help shape the roadmap for some of Google’s most critical Cloud products.
About the Role: Senior Software Developer, Machine Learning, Applied AI
The Cloud Applied AI team builds the portfolio of tools and experiences behind Gemini Enterprise, including the Shopping Agent, CX Agent Studio, Agent Assist, Vertex AI Search for Commerce, and Customer Experience Insights. The goal is bold: develop autonomous conversational AI agents capable of complex, open-ended dialogue and self-healing ecosystems. As a Senior Software Developer, you’ll be contributing to systems that affect how businesses across more than 200 countries interact with Google Cloud.
Beyond the technical work, this role requires strong stakeholder management, the ability to navigate ambiguity, and a willingness to mentor and coach your team. Google engineers here are expected to act like owners — anticipating customer needs, proposing solutions, and contributing to a broader culture of innovation and inclusion.
Benefits and Salary
For Canadian-based candidates, the salary range for this role is $182,000–$186,000 CAD, plus a 15% bonus target, equity (GSUs), and a comprehensive benefits package. Google’s benefits are well-regarded in the industry and cover a wide range of personal, financial, and professional support — visit Google’s benefits page for full details.
Job Details
🏢 Company: Google
📍 Location: Toronto, ON, Canada (also Waterloo, ON; Sunnyvale, CA; New York, NY)
📌 Job Type: Mid-level
💰 Pay: $182,000–$186,000 CAD + 15% bonus target + equity + benefits
Responsibilities
This role covers the end-to-end developer journey for AI Agents, requiring both deep technical execution and cross-functional leadership. You’ll be building meaningful ML systems while also guiding your team and influencing product strategy across Google Cloud’s Applied AI portfolio.
- Design and build recommendation systems specifically tailored for AI Agents
- Develop skill discovery and matching capabilities to enhance agent performance
- Implement investigative and diagnostic tools for monitoring and improving AI Agent outcomes
- Manage stakeholders effectively and resolve ambiguous technical challenges across teams
- Contribute to strategy and roadmap planning for the broader Applied AI team
- Coach and mentor team members, fostering a culture aligned with Google’s engineering values
Requirements / Skills
Google is looking for a technically well-rounded engineer who can move fluidly between ML infrastructure, product development, and team leadership. The ideal candidate brings both hands-on depth in machine learning systems and the interpersonal skills to thrive in a large, matrixed organization.
- Bachelor’s degree in a relevant field, or equivalent practical experience
- 5 years of software development experience, including testing and launching software products
- 3 years of experience in software design and architecture
- 5 years of ML-related experience in one or more areas: speech/audio, reinforcement learning, ML infrastructure, or another ML specialization
- 5 years of experience with ML design and infrastructure — including model deployment, evaluation, data processing, debugging, and fine tuning
- (Preferred) Master’s degree or PhD in Computer Science or a related technical discipline
- (Preferred) 3 years of technical leadership experience setting direction for project teams
- (Preferred) Experience working in complex, matrixed organizations on cross-functional or cross-business initiatives
How to Apply
To apply, use the link below to visit the official Google Careers posting. Make sure your resume is up to date and reflects your ML experience and any leadership roles before submitting.
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Job Summary & Tips for Applying
Quick Summary & What to Highlight: This Senior Software Developer, Machine Learning, Applied AI role at Google in Toronto is perfect for candidates who excel in ML infrastructure, agentic system design, and cross-functional technical leadership. On your resume, emphasize any experience with model deployment, fine-tuning, and AI agent development, along with your ability to work in a fast-paced environment. If you’ve previously worked in cloud AI, conversational AI, or reinforcement learning, 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 infrastructure, AI agents, and model evaluation that appear in the posting. Quantify your achievements where possible (e.g., “reduced model latency by 30%” or “led a team of 5 engineers across 3 ML product launches”). Write a brief cover letter expressing your genuine interest in Google and why you’re excited about contributing to Applied AI in Toronto. 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, recent Google Cloud announcements, and the Gemini Enterprise product suite beforehand. Prepare specific examples using the STAR method (Situation, Task, Action, Result) to demonstrate your ML engineering and leadership skills. Common questions may include scenarios about debugging complex ML systems, cross-team collaboration, and navigating technical ambiguity. Dress appropriately for a technology/software engineering environment, arrive 10–15 minutes early (or be ready early for virtual interviews), and bring copies of your resume. Prepare thoughtful questions about the role, team dynamics, and growth opportunities. After the interview, send a thank-you email within 24 hours reiterating your interest in the position.