Top Machine Learning Jobs in Ottawa

The role involves designing and implementing machine learning systems for knowledge representation and temporal reasoning, focusing on organizational intelligence. Responsibilities include building LLM-powered pipelines, developing memory algorithms, and researching various ML techniques.

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

Four-month, full-time research fellowship focused on ML systems and performance. Fellows build and evaluate infrastructure-heavy projects (e.g., CPU simulators, accelerator backends, large-scale distributed training), use external models/APIs, receive mentorship, funding for compute, and aim to produce public research outputs.

Design, build, and operate a cloud-native data and ML platform handling billions of events. Own end-to-end pipelines, feature stores, model training/serving, observability, and data product SLAs. Apply distributed systems, MLOps, and LLM/agentic systems to ensure reliable, low-latency access to features and production models with business-focused impact.

As a Sales Executive, you will hunt for new clients, manage enterprise accounts, and create revenue streams while collaborating with internal teams.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.