Machine Learning Engineer, Amazon Customer Service, Toronto

Machine Learning Engineer, Amazon Customer Service Amazon Customer Service is transforming how we deliver exceptional experiences to millions of customers worldwide, and we're seeking a Machine Learning Engineer to help build the next generation of intelligent solutions. You'll build Generative AI solutions to fulfill Amazon's mission to be Earth's most customer-centric company. Your work will empower leaders to take data-driven actions and give associates clear visibility into their personal impact on customer experience. You'll design, implement and scale production systems that empower associates and team managers to deliver their best work every day.

This is an opportunity to work on systems that operate at Amazon scale, processing vast amounts of data and translating complex signals into actionable information for stakeholders ranging from frontline associates to senior leadership. You'll build components that balance sophisticated analytics with intuitive user experiences, ensuring that insights are accessible and actionable for users with varying technical backgrounds. Your work will directly influence how we develop talent, recognize excellence, and continuously raise the bar for customer service quality across the organization.

Key job responsibilities

Apply generative AI techniques to surface meaningful patterns and personalized insights

Build components within scalable architectures that process customer interaction data

Design and deliver features end-to-end, from technical design through production deployment and operational support

Contribute to architectural decisions that balance innovation with operational excellence

Participate actively in code reviews, raising the quality bar for yourself and your teammates

Write clear technical documents including design proposals, operational runbooks, and post-incident reviews

Integrate emerging technologies, particularly generative AI and large language models, into production systems with guidance from senior engineers

Design and implement APIs and data models that support extensibility and long-term growth

Build monitoring and alerting to ensure the reliability of the systems you own

Collaborate with product managers, UX designers, and business stakeholders to translate requirements into well-scoped technical solutions

Identify and drive improvements to engineering processes, tooling, and operational practices within the team

A day in the life Throughout the day, you'll focus on hands‑on development of features and systems that shape how associates and managers understand their personal impact on customer satisfaction, while giving leadership insights into the quality of customer service we provide each day. Your morning might start with a quick win, like prototyping a GenAI agent to gather immediate feedback on a proposed solution. You'll discuss your approach with teammates and your tech lead to validate the design. In the afternoon, you attend a Lunch and Learn to stay on top of new emerging technology, before tackling a challenging problem with your peers.

About the team Engineers are empowered to build. Our team values a collaborative atmosphere that celebrates rapid innovation and meaningful impact. You'll find a culture of psychological safety where asking questions is encouraged, experimentation is valued, and learning from failures drives continuous improvement. We are deeply invested in your personal growth through peer collaboration and regular career development discussions. Mentorship flows in all directions, where senior engineers guide technical decisions while learning fresh perspectives from newer team members.

Basic Qualifications

3+ years of non‑internship professional software development experience

2+ years of non‑internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience

Experience programming with at least one software programming language

Preferred Qualifications

3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

Bachelor's degree in computer science or equivalent

Experience in debugging, profiling, and implementing software engineering best practices in large‑scale systems

Experience with Machine Learning and Large Language Model fundamentals, including prompt engineering, model evaluation, and integration of AI services into production applications

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life&AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well‑being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.

CAN, ON, Toronto– 114,800.00 – 191,800.00 CAD annually

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