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Added 14 hours ago
AH
Forklift operator trainer Quebec
Actualisation: HR Solutions for Businesses
Quebec, QC
- Internship
Linguistic requirements: Bilingual - Intermediate English*.
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LD
Intermediate Software Engineer
Leonardo DRS
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Intermediate computer skills including Outlook, Word, and Excel, ability to create and edit reports as required
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Canada
- Full-time
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General Dynamics Missions System International
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We are currently looking for a System Integration Verification & Validation Engineering Analyst, Intermediate to join our System Integration & Verification team. You will work as part of a…
Added 17 hours ago
GD
System Integration & Test, Intermediate
General Dynamics Missions System International
Ottawa, ON
- Full-time
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Added 17 hours ago
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Senior Mechanical Designer
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Added 18 hours ago
Senior Mechanical Designer
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Cambridge, ON
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Added 18 hours ago
TG
Intermediate Draftsperson - Toro
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LS
Intermediate Mechanical Engineer
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Added 21 hours ago
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MRI Technologist
RI-MUHC | Research Institute of the MUHC | #rimuhc
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An intermediate knowledge of oral and written English is required, as the position requires regular and complex contact with patients, researchers or international students who are…
Added 21 hours ago
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Laboratory Technician
RI-MUHC | Research Institute of the MUHC | #rimuhc
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Added 21 hours ago
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- $85,000 to $110,000 CAD / year
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Radio-Canada

AI Architect (T & I) (Telework/Hybrid)

Montreal, QC, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 1, 2026
Posting language: English
Posted: Oct 2, 2026

Original job description

Position Title

AI Architect (T & I) (Telework/Hybrid)

Status Of Employment

Contractee Long-Term (Durée déterminée)

Position Language Requirement

English, French

Language Skills

English (Reading - C - Advanced), English (Speaking - C - Advanced), English (Writing - B - Intermediate), French (Reading - C - Advanced), French (Speaking - C - Advanced), French (Writing - B - Intermediate)

Work at CBC/Radio-Canada

At CBC/Radio-Canada, we create content that informs, entertains and connects Canadians on multiple platforms. Our successes and accomplishments are driven by embodying and upholding values, which include creativity, integrity, inclusiveness and relevance.

Do you think you have the ability and drive to keep up with this exciting, ever-changing industry? Whether it be in front of the camera, on air, online or behind the scenes, you would be joining a team that thrives on making connections and telling stories that are important to Canadians.

Unposting Date

2026-07-21 11:59 PM

Behind the scenes, but ahead of the curve: help us develop the next-generation public service media organization.

Technology & Infrastructure (T&I) is the backbone and the future-forward arm of CBC/Radio-Canada. Our purpose is to constantly innovate to evolve and maintain the Corporation’s technology and infrastructure. We are the people that make stuff work. We make connections between media content, systems, people and places. We are the space in between.

A place with purpose. CBC/Radio-Canada has always been a highly regarded pioneer of media technology - not just in Canada but around the world. Today, we are transforming ourselves into a modern and agile public service media organization. Technology is the driving force, and we are the team making it happen.

This is a hybrid position with a mix of in-office and remote work. Work arrangements will be discussed with hiring managers per departmental guidelines.

Your Role

If you want to push the boundaries of media technology and are excited by the challenge of bridging creativity with cutting-edge tech, this role is for you!

As a key member of the Architecture and Strategic Development (Media System Architecture) team, you will design and plan CBC/Radio-Canada’s future technology infrastructure. Our mission is to transform our disparate media workflows by integrating hybrid agents, video understanding systems and advanced artificial intelligence architectures operating 24/7.

We are looking for an AI Architect with deep technical expertise in optimizing training and inference for large language models (LLMs), multimodal models and AI systems in a media context. As a technical thought leader, you will design robust systems to make AI faster, more scalable and more reliable, ensuring their seamless integration into our critical production ecosystems (PAM, MAM, studios).

Your Responsibilities

Optimizing Models, Inference and GPU Infrastructure

Design and build high-performance training and inference systems for LLMs and multimodal AI models.
Optimize end-to-end training, including high throughput data pipelines (streaming, sharding, bucketing), distributed training (parallelism strategies) and mixed precision.
Optimize inference and serving engines to guarantee minimum latency using KV caching design/management, batching, quantization and long-context processing.
Collaborate with the Technology & Infrastructure (T&I) team to design, right-size and evolve our internal GPU cluster into a new-generation infrastructure capable of supporting these massive workloads.

Strategy, Architecture and Media Ecosystem

Plan, develop and architect the integration of AI solutions within CBC/Radio-Canada’s media production environments (PAM, MAM, television and radio studios).
Evaluate and standardize integration protocols such as Model Context Protocol (MCP) and agent-to-agent (A2A) architectures to interconnect our models with complex production platforms (Avid, Dalet, Adobe).
Ensure absolute data security while developing video understanding systems that can interact with both file-based workflows (codecs, wrappers) and IP live workflows (SMPTE‑2110).

Technical Leadership, Mentoring and MLOps

Provide expert guidance on system efficiency, spearheading initiatives to dramatically improve architectural scalability, latency and reliability.
Mentor and elevate the organization’s engineers and data scientists in large-scale ML system design and performance engineering.
Develop robust MLOps/LLMOps pipelines with a constant focus on observability, performance profiling and automated testing.
Summarize and explain technological innovations to make them understandable to decision-makers and production teams and influence our strategic investments.

Featured Technology Environment

Inference Modelling and Optimization: PyTorch, vLLM, DeepSpeed, Accelerate, KV caching architectures, quantization techniques.
Infrastructure, Cloud and Compute: internal GPU clusters, distributed architectures, AWS, Azure, GCP, containers, Kubernetes.
Orchestration and Agents: Open WebUI, integration protocols (MCP, A2A), LiteLLM, LangChain, LangGraph, Strands.
Media Production: SMPTE-2110 protocols, PAM/MAM (Avid Interplay, Dalet), Adobe suite, media processing (audio/video codecs).
MLOps and Observability: Langfuse, Weights & Biases (W&B), MLflow, performance profiling tools.

Minimum Qualifications

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.

Nice-to-Have Skills (Assets)

Experience with modern video software architectures (e.g., NVIDIA Holoscan for Media) or ultra-high-performance IP transfer protocols.
Demonstrated experience managing complex workflows through cloud or hybrid data pipelines.
Active contributions to open-source high-performance AI projects and published research, or deep understanding of security frameworks for responsible AI.

Candidates may be subject to skills and knowledge testing.

We thank all applicants for their interest, but only candidates selected for an interview will be contacted.

As part of our recruitment process, candidates who advance to the next

step will be asked to complete a background check. This includes:

A mandatory Criminal record check.
Other background checks may be conducted based on the operational requirements of the position.

CBC/Radio-Canada is committed to being a leader in reflecting our country’s diversity. That’s because we can only create and tell the stories that connect Canadians, by having a workforce that mirrors the ever-changing makeup of our country. That’s why we, as an employer, value equal opportunity and nurture an inclusive workplace where our individual differences are not only recognized and valued, but also extend to and pervade all the services we provide as Canada’s public broadcaster. For more information, visit the Diversity and Inclusion section of our website. If you have accommodation needs at this stage of the recruitment process, please inform us as soon as possible by sending an e-mail to recruitment@cbc.ca.

You are invited to consult and familiarize yourself with our Code of Conduct, which can be found on our corporate website. All employees must adhere to the Code as a condition of employment. We also invite you to take a look at our policy on conflicts of interest. In the event that you become an employee, it will be important to inform us, as quickly as possible, of any situation that, because of your hiring, constitutes or could appear to constitute a conflict of interest.

Primary Location:

1000, Rue Papineau, Montreal, Quebec, H2K 0C2

Number Of Openings

1

Work Schedule

Full time

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More about this job

Responsibilities

Design and optimize high-performance training and inference systems for large language and multimodal models, and help evolve GPU infrastructure to support large-scale AI workloads. Architect secure AI integrations for CBC/Radio-Canada’s media production systems, lead MLOps and performance initiatives, mentor technical teams, and communicate architecture decisions to stakeholders.

Requirements

Requires a bachelor’s or master’s degree in a relevant technical or scientific field, functional English-French bilingualism, at least five years of AI/ML experience, and at least eight years in software engineering. Candidates should have experience with language models, scalable enterprise AI, cloud and orchestration platforms, MLOps, and media production systems in highly available environments.

Skills

AI Architecture
Large Language Models
Multimodal AI
Model Training and Inference Optimization
Distributed Training
GPU Infrastructure
PyTorch
vLLM
DeepSpeed
Kubernetes
MLOps and LLMOps
Media Production Systems
PAM and MAM Integration
Model Context Protocol
AI Agent Architectures
English and French Bilingualism

Visa sponsorship

Not detected in the job text

Keywords

Artificial Intelligence
Machine Learning
Large Language Models
Multimodal Models
PyTorch
vLLM
DeepSpeed
Hugging Face
GPU Clusters
Distributed Training
Inference Optimization
Quantization
KV Caching
Kubernetes
Docker
AWS
Azure
Google Cloud Platform
MLOps
LLMOps
CI/CD
Model Context Protocol
Agent-to-Agent Architecture
LangChain
LangGraph
PAM
MAM
SMPTE 2110
Avid Interplay
Dalet

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