AI Architect – T & I

Jobtailor; Montreal (administrative region); On-site; CAD 150,000 - 210,000; Full time

Job summary

CBC/Radio-Canada is seeking an experienced AI/ML Infrastructure Architect to design and evolve our future technology infrastructure, optimize GPU clusters, and build scalable training and inference systems for LLMs and multimodal models.

You will collaborate with the Technology & Infrastructure team, mentor engineers and data scientists, and drive cost-efficient, enterprise-grade AI solutions in a 24/7 media production environment. Bilingual English/French required.

Qualifications

• Bachelor's or master's in software engineering, IT, AI, mathematics or related field.
• Functional bilingualism (English & French) essential for Canada-wide communications.
• 5+ years proven experience developing and deploying AI/ML solutions.
• 8+ years building tools and platforms in a software engineering role.
• Experience with language models and scalable, cost-efficient AI solutions.
• Strong knowledge of LLM, RAG and AI agent architectures.
• Experience selecting AI frameworks (TensorFlow, PyTorch, Hugging Face) and clouds (Azure, AWS, GCP).
• Knowledge of MLOps, DevOps and CI/CD pipelines.
• Media production platforms experience; 24/7 highly available environments.
• Cloud, virtualization, networking and storage knowledge.

Responsibilities

• Design and plan CBC/Radio-Canada’s future technology infrastructure.
• Optimize models, inference and GPU infrastructure.
• Build high-performance training and inference systems for LLMs and multimodal AI models.
• Collaborate with the Technology & Infrastructure team to evolve internal GPU cluster.
• Plan integration of AI solutions within media production environments.
• Mentor and elevate engineers and data scientists in large-scale ML system design and performance engineering.

Skills

AI/ML Solution Development

Large-Scale ML System Design

Cloud Platform Experience

AI Frameworks

Bilingual Communication

GPU Infrastructure Optimization

MLOps

DevOps

Inference Systems Design

Technical Documentation

Education

Bachelor's or master's degree in software engineering / AI / IT / mathematics

Tools

Docker

Kubernetes

TensorFlow

PyTorch

Hugging Face

Azure

AWS

GCP

CI/CD

Job description

• Design and plan CBC/Radio-Canada’s future technology infrastructure
• Optimize Models, Inference and GPU Infrastructure
• Design and build high-performance training and inference systems for LLMs and multimodal AI models
• Collaborate with the Technology & Infrastructure (T&I) team to design, right-size and evolve our internal GPU cluster
• Plan and develop the integration of AI solutions within CBC/Radio-Canada’s media production environments
• Mentor and elevate the organization’s engineers and data scientists in large-scale ML system design and performance engineering

Requirements

• Bachelor's or master's degree in software engineering, information technology, artificial intelligence, mathematics or a related natural science field
• Functional bilingualism (English and French) essential for Canada-wide communications
• At least five years’ proven experience developing and deploying AI/ML solutions
• At least eight years’ experience building tools and platforms in a software engineering role
• Demonstrated experience working with language models and designing solutions optimized for cost efficiency and scale
• Strong conceptual understanding of LLM, RAG and AI agent architectures, including their frameworks and operational constraints
• Experience selecting AI framework architectures (e.g., TensorFlow, PyTorch, Hugging Face), cloud platforms (Azure, AWS, GCP) and orchestration tools (Docker, Kubernetes) for scalable enterprise AI solutions
• Knowledge of ModelOps, AI engineering, DevOps and MLOps practices (including CI/CD pipelines)
• Solid understanding of machine learning and deep learning fundamentals
• Strong technical documentation skills, with the ability to produce diagrams, demos and technical artifacts that make AI architectures understandable and actionable
• Hands-on technical experience working with media production platforms (MAM/PAM) and designing scalable solutions in a highly available, 24/7 environment
• Solid working knowledge of cloud technologies (AWS, Azure or GCP), virtualization, networking and storage.

Core Competencies

Demonstrates expertise in designing and optimizing AI/ML solutions, with a strong focus on large-scale system architecture and performance engineering. Proficient in integrating AI technologies within media production environments while mentoring engineering teams.

Highest-signal resume keywords

• AI/ML Solution Development
• Large-Scale ML System Design
• Cloud Platform Experience (AWS, Azure, GCP)
• AI Frameworks (TensorFlow, PyTorch, Hugging Face)
• Bilingual Communication (English and French)

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Deep Learning
• ModelOps
• AI Engineering
• DevOps
• MLOps
• Technical Documentation
• Cost Efficiency Optimization
• Inference Systems Design
• GPU Infrastructure Optimization

Soft Skills

• Mentoring
• Collaboration
• Communication

Industry Keywords

• AI Solutions Integration
• High-Performance Training Systems
• Language Models
• Operational Constraints
• Scalable Enterprise AI Solutions

Tools & Technologies

• Docker
• Kubernetes
• Media Production Platforms (MAM/PAM)
• CI/CD Pipelines
• Virtualization
• Networking
• Storage