Top Machine Learning Jobs in Ottawa

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.

As a Senior Machine Learning Engineer, you'll design and implement ML models, develop data pipelines, and collaborate on AI features at Mural.

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

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.

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.

Design and optimize machine learning pipelines for large-scale systems, integrating models into user features and ensuring data integrity and performance.

Lead the design and optimization of ML systems at Scribd, managing cross-team projects, mentoring engineers, and shaping technical direction for ML initiatives.

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.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

The Senior AI/ML Engineer will architect, build, and deploy AI systems, working with clients to understand their needs and applying MLOps practices to enhance AI services.

As a Full Stack Engineer, you'll develop production-ready AI and ML features, build APIs, design scalable systems, and implement frontend solutions using Angular.

As a Founding Engineer at Outspeed, you will develop and optimize TTS models, enhance speech quality, and engage with customers for system improvements.

The Senior ML Performance Engineer will architect a Performance Testing Platform, optimize ML performance on GPUs, and validate model efficiency.

Develop scalable machine learning models, collaborate with teams, create proofs of concepts, and write maintainable code while engaging in the entire ML development cycle.

Develop AI solutions and enhance observability data using AI-powered features. Collaborate cross-functionally, iterate rapidly, and take ownership of AI projects while ensuring scalability and impact.

As a Senior Machine Learning Developer, you'll enhance the deployment and lifecycle of machine learning models, ensuring they function effectively at scale and meet high reliability standards.

The Machine Learning Engineer will develop and deploy ML models, leveraging analytical skills to automate processes and reveal data value.

The Senior Machine Learning Engineer will design and optimize ML/AI systems, lead model development, and collaborate cross-functionally to advance digital forensics.

The AI/ML Engineer will design and develop AI-powered applications, automate workflows, and integrate AI into BPM's daily operations, ensuring they deliver business value.

As a Machine Learning Engineer, you will develop models for NLP and code-generation systems, analyze data, and improve AI performance using advanced algorithms. You'll manage the entire ML lifecycle and ensure effective communication of model benefits across the organization.

Lead the development and deployment of advanced machine learning models focusing on NLP, while ensuring model integrity and communication with stakeholders.

As a Machine Learning Engineer/Scientist, you will develop ML systems for cryopreservation research, manage data pipelines, and deploy models for scientific insight.

The role involves developing ML systems for enterprise workflows, focusing on user understanding, task prediction, and optimizing ML pipelines. Key responsibilities include designing scalable evaluation frameworks and collaborating with teams to deliver production-ready solutions.