Machine Learning/GenAI Engineering Manager

PRICELINE CAREERS; Toronto; Hybrid; CAD 160,000 - 185,000; Full time

Job summary

Priceline Careers in Toronto is seeking an experienced Machine Learning/GenAI Engineering Manager to lead a high-performing team and drive the architecture of a centralized AI platform. You will guide model training, evaluation, deployment, and monitoring across product lines, balancing innovation with reliability.

The role requires 3+ years in ML engineering leadership, 5+ years building ML platforms, strong cloud and DevOps skills, and a collaborative, cross-functional approach.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or related quantitative field.
• 3+ years of technical engineering management or direct team leadership in ML, Data Platform, or Infrastructure.
• 5+ years building and scaling ML platforms, MLOps pipelines, or cloud-based data systems.
• Proven experience leading GenAI and ML projects including training, evaluation, and deployment.
• Strong cloud (GCP preferred), Kubernetes/Docker, and infrastructure automation (Terraform).

Responsibilities

• Lead and grow a hybrid team of ML engineers and MLOps developers.
• Define the platform roadmap for a centralized, self-service AI/ML platform.
• Own shared tooling for model evaluation, observability, MCP, and LLM gateways.
• Collaborate with data science leads, product, security, and engineering leaders to align needs.
• Establish MLOps and LLMOps best practices for high availability and cost control.

Skills

Leadership

ML Platform

MLOps

Cloud Computing

Kubernetes

Docker

Education

Bachelor’s degree in Computer Science / related field

Master’s degree (preferred)

Tools

Terraform

GCP

LLM gateways

Job description

Machine Learning/GenAI Engineering Manager

R5823

Location

Toronto

Technology

Machine Learning/GenAI Engineering Manager

This role is eligible for our hybrid work model: 2 days in-office

This job posting is for an existing, currently vacant position.

Machine Learning /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).

Leadership Experience: 3+ years of experience in technical engineering management or direct team leadership roles within ML, Data Platform, or Infrastructure engineering.

Hands-on Platform Experience: 5+ years of hands-on experience building, scaling, and maintaining ML platforms, MLOps pipelines, or cloud-based data systems.

ML & GenAI Domain Knowledge: Proven track record leading projects that support both traditional machine learning lifecycles (experiments, training, registry, inference) and modern GenAI architectures (RAG, fine-tuning, orchestration, LLM gateways).

Infrastructure & Cloud: Strong technical background in cloud platforms (GCP preferred), containerization (Kubernetes, Docker), and infrastructure automation (Terraform).

Tooling & Observability: Demonstrated experience establishing developer-facing tooling, monitoring, and evaluation frameworks for AI workloads.

Communication: Excellent communication skills with the ability to bridge technical concepts between data scientists, platform engineers, and executive leadership.

Preferred Qualifications

Advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, Data Science, or Artificial Intelligence.

Experience designing or evaluating emerging GenAI standards, such as MCP, modern agentic frameworks, or API gateway patterns for LLMs.

Background in managing mixed-skill technical teams across both application engineering and core platform infrastructure.

Familiarity with data security, privacy compliance, and cost governance in large-scale cloud AI deployments.

There are a variety of factors that go into determining a salary range, including but not limited to external market benchmark data, geographic location, and years of experience sought/required. In addition to a competitive base salary, certain roles may be eligible for an annual bonus and/or equity grant.

The salary range for this position is $160,000K - $185,000K CAD.