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Machine Learning/GenAI Engineering Manager
Priceline.com
Toronto, CAN
Full-time
Onsite
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Machine Learning And Genai Engineering Manager
Our Technology team is the backbone of our company: constantly creating, testing, learning and iterating to better meet the needs of our customers.
If you thrive in a fast-paced, ideas-led environment, you’re in the right place.
Why this job’s a big deal:
We are looking for an ML/GenAI Engineering Manager to lead and grow a high-performing team of 7 ML Platform and MLOps developers.
In this role, you will lead the creation and scaling of a unified, centralized ML and GenAI platform used by data scientists across various product teams.
You will drive the architecture and delivery of core infrastructure supporting both traditional ML model training/deployment and cutting-edge GenAI applications, while owning key shared tools like evaluation, monitoring, MCP integration, and LLM gateways.
In this role, you will get to:
- People & Team Leadership: Lead, mentor, and advocate for a hybrid team of 7 ML Engineers and MLOps developers. Set clear goals, manage performance, and foster a strong culture of technical excellence and continuous learning.
- Platform Vision & Strategy: Drive the roadmap for a centralized, self-service AI/ML platform that simplifies model training, evaluation, deployment, and monitoring across all product lines.
- GenAI Infrastructure & Tooling: Own and standardize enterprise shared AI development tooling, including model evaluation frameworks, observability, safety monitoring, MCP (Model Context Protocol), and LLM gateway integrations.
- Cross-Functional Collaboration: Partner closely with data science leads, product managers, security teams, and engineering leaders to align platform capabilities with business needs and technical standards.
- Operational Excellence: Establish robust MLOps and LLMOps best practices, ensuring high availability, scalable infrastructure, cost optimization, and enterprise-grade security for all deployed models and APIs.
Who you are:
- Education: Bachelor’s degree in Computer Science, Software Engineering, or a closely related quantitative field (or a Master’s degree in a related technical discipline).
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