AI Architect (T and I) (Remote/Hybrid)

Job Title: AI Architect (T and I) ... Job Type: PermanentLanguage Requirements for the Position: English, FrenchLanguage Skills:

English (Writing - C - Advanced), English (Oral Expression - C - Advanced), English (Reading - C - Advanced), French (Writing - C - Advanced), French (Oral Expression - C - Advanced), French (Reading - C - Advanced)Work at CBC/Radio-Canada

At CBC/Radio-Canada, we create content that informs, entertains, and brings Canadians together across multiple platforms. Promoting and embodying values such as creativity, integrity, inclusion, and relevance drive our achievements.

Do you think you have what it takes to succeed in this exciting and ever-evolving environment? Whether in front of the camera, on-air, online, or behind the scenes, you would be part of a team that thrives on connecting with the Canadian public and telling stories that matter to them.

Application Deadline: 2026-08-03 11:59 PMBehind the Scenes, but Always at the Forefront: Help Us Develop Next-Generation Public Service Media.

The Technology and Infrastructure (T and I) team is the foundation that CBC/Radio-Canada relies on to propel itself into the future. Our mission is to constantly innovate to evolve and maintain technologies and infrastructures. We ensure everything runs smoothly. We connect media content, systems, people, and places. We are the space where ideas and actions meet.

A mission with meaning. CBC/Radio-Canada has always been recognized as a leader in media technologies, not only in Canada but worldwide. Today, we are transforming our operations to remain an agile and modern public service media. Technology is the engine of this change, and we are the team bringing it to life.

This position is a combination of remote work and office presence. Work arrangements will be discussed with hiring managers according to guidelines determined by the sector.

Your Mandate

If you enjoy pushing the boundaries of media technologies and are challenged by the task of merging creativity with cutting-edge technology, this position is for you.

Within the Media System Architecture team, you will be responsible for designing and planning CBC/Radio-Canada's future technological infrastructure. Our mission is to transform our heterogeneous media workflows by integrating hybrid agents, video understanding systems, and cutting-edge AI architectures operating 24/7.

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

Your Responsibilities

Model Optimization, Inference, and GPU Infrastructure

• Design and build highly performant training and inference systems for LLMs and AI multimodal models.
• Optimize end-to-end training: high-throughput data pipelines (streaming, sharding, bucketing), distributed training (parallelism strategies), and mixed precision.
• Optimize inference and serving to ensure minimal latency: cache KV design and management, batching, quantization, and long-context handling.
• Collaborate with the Technology and Infrastructure (T&I) team to design, scale, and evolve our internal GPU cluster into a next-generation infrastructure capable of supporting these massive workloads.

Strategy, Architecture, and Media Ecosystem

• Plan, develop, and design the integration of our AI solutions within CBC/Radio-Canada's media production systems (PAM, MAM, TV and radio studios).
• Evaluate and standardize integration protocols (e.g., Model Context Protocol [MCP], 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 capable of interacting with our file-based (codecs, wrappers) and IP-based (SMPTE-2110) streams.

Technical Leadership, Mentoring, and MLOps

• Act as an expert advisor for system efficiency, leading initiatives that significantly improve scalability, latency, and reliability of our architectures.
• Mentor and uplift engineers and scientists in the company on the design of large-scale ML systems and performance engineering.
• Establish rigorous MLOps/LLMOps pipelines with a constant focus on observability, performance profiling, and automated testing.
• Synthesize and popularize technological innovations to influence our strategic investments and make them accessible to decision-makers and production teams.

Preferred Technological Environment

• Modeling & Inference Optimization: PyTorch, vLLM, DeepSpeed, Accelerate, KV cache architectures, quantization techniques.
• Infrastructures, Cloud & Compute: Internal GPU clusters, distributed architectures, AWS, Azure, GCP, containers, Kubernetes.
• Orchestration & 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 & Observability: Langfuse, Weights & Biases (W&B), MLflow, performance profiling tools.

Minimum Qualifications

• Bachelor's or Master's degree in software engineering, computer science, artificial intelligence, mathematics, or a related field in natural sciences.
• Functional bilingualism (French and English) essential for pan-Canadian communication.
• Minimum of five (5) years of proven experience in developing and implementing AI/ML solutions.
• Minimum of eight (8) years of experience in developing tools or platforms in a software engineering role.
• Demonstrated experience with language models, designing solutions optimized for cost efficiency and scalability.
• Conceptual understanding of LLM, RAG, and AI agent architectures, including their framing and operational constraints.
• Experience in selecting and architecting AI frameworks (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 (e.g., CI/CD pipelines).
• Strong understanding of machine learning and deep learning.
• Strong documentation skills, with the ability to produce diagrams, demonstrations, and technical artifacts that make AI architectures understandable and actionable.
• Technical experience with media production platforms (MAM/PAM) and designing scalable solutions in a 24/7 highly available environment.
• Functional knowledge of cloud technologies (AWS, Azure or GCP), virtualization, networking, and storage.

Desired Qualifications (Assets)

• Experience with modern video software architectures (e.g., NVIDIA Holoscan for Media) or high-performance IP transfer protocols.
• Proven experience in managing complex workflows through cloud or hybrid data pipelines.
• Active contributions to open-source AI performance projects, research publications, or strong knowledge of responsible AI security parameters.

The skills and knowledge of candidates may be subject to testing.

We thank all candidates for their interest, but we will only communicate with those selected for an interview.

As part of our recruitment process, all candidates selected for the background check stage will be subject to