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

CBC/Radio-Canada

$100K — $130K *
Media
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor’s or master’s degree in software engineering, IT, AI, mathematics or related field.
  • Fluent in English and French for effective communications across Canada.
  • Five years’ experience in developing and deploying AI/ML solutions.
  • Eight years’ experience in software engineering, specifically building tools and platforms.
  • Proven track record in working with language models and cost-efficient scalable solutions.
  • Strong understanding of LLM, RAG, and AI agent architectures and their operational constraints.
  • Hands-on experience with media production platforms (MAM/PAM) and designing scalable solutions.

Responsibilities

  • Design and build high-performance training and inference systems for large language and multimodal AI models.
  • Optimize data pipelines for efficiency using streaming, sharding, and distributed training techniques.
  • Enhance inference engines for low-latency performance through innovative caching and processing methods.
  • Collaborate with teams to evolve internal GPU infrastructure to support massive workloads for AI applications.
  • Architect the integration of AI solutions within media production environments for TV and radio.
  • Standardize protocols for model interaction with production platforms, ensuring data security.
  • Mentor engineering teams in large-scale ML design and focus on developing robust MLOps pipelines.

Benefits

  • Telework/Hybrid work arrangements available.
  • Opportunities for professional development and technical mentoring.
  • Engagement in cutting-edge AI technologies and media production innovations.
  • Contributions towards transforming the media technology landscape.
  • Work in a collaborative environment that encourages creativity alongside technology.
Full Job Description

Position Title:

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

Status of Employment:

Permanent

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)

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.

Primary Location:

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

Number of Openings:

1

Work Schedule:

Full time

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