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

6 days ago

Toronto, Canada +2 moreStaff+

Responsibilities

Design and build high-performance training and inference systems for LLMs and multimodal AI models.
Optimize data pipelines, distributed training, mixed precision, inference serving, batching, quantization, KV caching, and long-context processing.
Design and evolve internal GPU-cluster infrastructure for large-scale AI workloads.
Architect AI integrations with media production environments, including PAM, MAM, studios, Avid, Dalet, and Adobe.
Evaluate and standardize MCP and A2A integration architectures for complex production platforms.
Develop video-understanding systems supporting file-based and IP live workflows, including codecs, wrappers, and SMPTE-2110.
Provide technical leadership on scalability, latency, reliability, performance profiling, and system efficiency.
Mentor engineers and data scientists in large-scale ML system design and performance engineering.
Develop MLOps and LLMOps pipelines with observability and automated testing.
Explain technical innovations to decision-makers and production teams and influence strategic investments.

Bachelor’s or master’s degree in software engineering, information technology, artificial intelligence, mathematics, or a related natural science field.
At least five years of proven experience developing and deploying AI/ML solutions.
At least eight years of experience building tools and platforms in a software engineering role.
Demonstrated experience with language models and designing cost-efficient, scalable AI solutions.
Strong understanding of LLM, RAG, and AI-agent architectures, frameworks, and operational constraints.
Experience selecting AI frameworks, cloud platforms, and orchestration tools for scalable enterprise AI solutions.
Knowledge of ModelOps, AI engineering, DevOps, and MLOps practices, including CI/CD pipelines.
Solid machine-learning and deep-learning fundamentals.
Strong technical documentation skills, including diagrams, demos, and technical artifacts.
Hands-on experience with media production platforms and scalable, highly available 24/7 solutions.
Working knowledge of cloud technologies, virtualization, networking, and storage.
Functional bilingualism in English and French.
Preferred qualifications include NVIDIA Holoscan for Media or high-performance IP-transfer experience, cloud or hybrid data-pipeline workflow management, open-source AI contributions, published research, or deep knowledge of responsible-AI security frameworks.
Candidates may be subject to skills and knowledge testing and a criminal-record background check.

Permanent, full-time position.
Hybrid work arrangement combining in-office and remote work, with details discussed according to departmental guidelines.
Work location is CBC/Radio-Canada’s Montreal, Quebec office.
Inclusive workplace and accommodation support are provided during recruitment.

5,001-10,000 employees