Top Machine Learning Jobs in Ottawa

The ML Engineer will develop and enhance machine learning models for credit decisioning, drive technical innovation, and collaborate across teams to deliver impactful solutions for small businesses.

You will build a search and assistant product, improve personalization, train models, and write robust code while mentoring junior engineers.

The AI/ML Engineer will design, develop, and optimize machine learning models for mobile applications, collaborating with teams to enhance user experiences and innovate in AI-driven solutions.

The AI/ML Engineer will develop and optimize machine learning models, work with cross-functional teams, and enhance mobile app features.

As an AI/ML Engineer, you'll develop and optimize machine learning models for mobile applications, collaborate with teams, and integrate AI-driven features to enhance user experience.

The role involves solving customer problems by building ML solutions, engaging with various stakeholders, and taking ownership of the outcome through deployment.

The role involves building production ML models for voice AI, focusing on fine-tuning, deploying, and evaluating models to enhance human-like interactions.

The role involves designing and implementing MLOps pipelines, optimizing machine learning processes, and ensuring model performance and compliance in a collaborative environment.

The Databricks ML Administrator will manage ML environments, oversee governance, secure operations, and ensure reliable model training and deployment.

As a Principal Software Engineer II, you will build and maintain machine learning components for Elasticsearch, optimizing model performance and collaborating with various engineering teams on advanced analytics.

Lead technical direction and execution of CX automation systems to reduce support costs and speed resolution. Architect scalable backend services, decision engines, and workflows that take real actions with fraud/abuse guardrails. Partner with Product and CX Operations, drive platform investments, and measure automation effectiveness.

Lead design and deployment of production-grade AI solutions, build multi-agent systems and cloud-native ML infrastructure, apply rigorous statistical evaluation, implement generative and predictive models, champion MLOps and data pipeline best practices, and collaborate with clients to translate business needs into technical solutions.

As a Machine Learning Engineer, develop ML models, data pipelines, conduct analytics, and work on image and video inference for fish health and behavior.

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

The Senior Data Engineer will develop and deploy machine learning models, build end-to-end ML pipelines, optimize performance, and collaborate across teams to enhance AI capabilities at ClickUp.

Design and build agentic AI workflows for biological and clinical data curation and analysis. Implement context engineering (RAG variants), prompt and agent architecture optimization, LLM tool-use integrations, and evaluation benchmarks. Collaborate with bioinformatics and clinical experts to translate domain problems into reliable, production-quality agentic systems.

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.

Design and implement machine learning algorithms for robotic manipulation, focusing on RL and IL. Collaborate across disciplines to ensure integration and successful deployment.

This internship involves developing machine learning approaches for biological data, designing experiments, collaborating on research, and presenting findings.

The role involves developing high-performance AI features for observability, rapid prototyping, and cross-functional collaboration, aimed at improving incident response and system behavior understanding.

Build and deploy production-quality AI Agents and proprietary LLMs, improve reasoning/planning and evaluation, scale AI systems, collaborate with engineering teams, and enhance security, cost-efficiency, and reliability.

Lead Lime's ML Center of Excellence, set ML infrastructure and standards, guide model lifecycle, deploy and monitor production ML, build reusable features, mentor teams, and partner with engineering to scale reliable ML systems.

The role involves building scalable ML models, mentoring engineers, translating business requirements into specs, and ensuring solutions meet performance constraints.

Design, build, and deploy scalable ML solutions using GCP and Vertex AI. Collaborate with teams to operationalize models and monitor performance.

Responsible for designing experiments to evaluate AI models, developing evaluation methodologies, analyzing performance data, and collaborating on production insights.