Staff Machine Learning Engineer - Toronto, Ontario, Canada

Staff Machine Learning Engineer - Toronto, Ontario, Canada

Toronto

PagerDuty empowers teams of all kinds to do the critical work that moves business forward through the PagerDuty Operations Cloud.

We are on the hunt for a formidable Staff Machine Learning (ML) Engineer who is not only adept at architecting state-of-the-art AI initiatives but who is also ready to mentor and inspire a team composed of Machine Learning, Data Scientists, and Software Engineers.

In this role, you will actively contribute to and lead AI-first innovation across our customers' Operations powered by ML and Agentic AI solutions. You will be instrumental in developing groundbreaking proofs of concept, contributing to our AI strategy, and pushing the boundaries of what's possible—all while addressing critical short and long-term team goals.

In a world where customer adoption of new technologies is uncertain and competition is fierce, we need Staff Engineering leaders who thrive under pressure, are capable of operating at different levels of altitude, and pave the way for a future where our products not only meet but exceed the aspirations of our existing and future customers.

Key Responsibilities:

• Build and improve the capabilities of the data platform that enable and accelerate the production of ML/AI-based solutions.
• Drive and define standards for AI/ML across the organization.
• Provide guidance, technical leadership, and mentoring to other members of the team.
• Mentor junior members and participate in scaling up the existing team.
• Proactively recommend improvements and new approaches addressing potential systemic pain points and technical debt.
• Anticipate technical demands on the data platform based on the organization’s roadmap and systematically drive the evolution of the architecture toward those ends.
• Develop a long-term plan for ML/AI investments.
• You have 8+ years of experience building, designing, and evolving data architecture for large-scale systems.
• Experience working with Product teams, ensuring and driving a timely delivery.
• Have a deep understanding of the trade-offs to be considered when designing and delivering machine learning solutions to production.
• Experience leading cross-team architecture discussions, building technical prototypes, and driving the adoption of best practices across diverse teams.
• Demonstrated experience with data engineering processes, working with unstructured data and cloud-based data infrastructures.
• Passionate about ML engineering and interested in driving discussions with stakeholders and executives.

Preferred Requirements:

• Desire to keep learning new concepts and adapt to the start-of-the-art.
• Experience shipping reliable and scalable AI/ML products.
• Prior experience in a SaaS environment.
• Awareness of and experience with ML processes (exploration, training, testing, deployment, monitoring), technologies (services, packages), and ML Operations.
• Experience not only developing POC’s / new products, but developing products that customers are adopting and using at large scale.
• A strong record of published work in technical forums, contributions to open source projects, or research innovations.

The base salary range for this position is 156,000 - 232,000 CAD. This role may also be eligible for bonus, commission, equity, and/or benefits.

This role is expected to come into our Toronto office 1 day/month so you can thrive in your new role and fully embrace being a Dutonian!

Apply anyway! We extend opportunities to a broad array of candidates, including those with diverse workplace experiences and backgrounds. Whether you're new to the corporate world, returning to work after a gap in employment, or simply looking to take the next step in your career path, we are excited to connect with you.

About PagerDuty

PagerDuty, Inc. (NYSE:PD) is a global leader in digital operations management. The PagerDuty Operations Cloud revolutionizes how critical work gets done, and powers the agility that drives digital transformation. Customers rely on the PagerDuty Operations Cloud to compress costs, accelerate productivity, win revenue, sustain seamless digital experiences, and earn customer trust. More than half of the Fortune 500 and more than two thirds of the Fortune 100 trust PagerDuty including Cisco, Cox Automotive, DoorDash, Electronic Arts, Genentech, Shopify, Zoom and more.

PagerDuty is committed to creating a diverse environment and is an equal opportunity employer. PagerDuty does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, parental status, veteran status, or disability status.