Staff ML Engineer — Lead Production ML at Scale (Hybrid)

OpenTable; Toronto; Hybrid; CAD 130,000 - 190,000; Full time

Benefits offered by this job

Hybrid work model

Health and dental insurance

Paid time off

Career development

Travel discounts

Parental leave

On-demand learning

Employee resource groups

Job summary

OpenTable in Toronto is seeking a Staff Machine Learning Engineer to set the technical direction for building, serving, and operating ML systems in production. You will partner with ML Scientists and engineers to move models from experimentation to reliable, monitored production services, shaping standards for the team.

This is an engineering-forward role focused on production systems, with opportunities to influence across a global team and a portfolio spanning diners, restaurants, and internal

Qualifications

• 7+ years building and operating production ML systems.
• Experience across multiple ML orgs and reference architectures.
• Hands-on with a major cloud platform and model serving.
• Strong Python and a statically typed language (Java).
• Production MLops ownership including monitoring and rollback.

Responsibilities

• Define technical direction for serving, deployment, and monitoring of models.
• Deliver high-throughput, low-latency production ML services.
• Set engineering standards: testing, CI/CD, observability, on-call practice.
• Collaborate with PMs and stakeholders to scope and prioritize work.
• Lead multi-quarter projects and influence broader engineering decisions.

Skills

Python

Java

Distributed Systems

MLOps

Cloud Platforms

Leadership

Production ML

LLMs

Tools

AWS

GCP

Azure

CI/CD

Observability

Job description

OpenTable in Toronto is seeking a Staff Machine Learning Engineer to set the technical direction for building, serving, and operating ML systems in production. You will partner with ML Scientists and engineers to move models from experimentation to reliable, monitored production services, shaping standards for the team.

This is an engineering-forward role focused on production systems, with opportunities to influence across a global team and a portfolio spanning diners, restaurants, and internal