Top Machine Learning Jobs in Ottawa

The Senior Machine Learning Engineer will design and optimize ML discovery features, oversee projects, mentor engineers, and manage the ML lifecycle from data ingestion to model deployment.

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.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

Contribute to developing machine learning models for multi-scale biology, focusing on design, deployment and optimization across teams and technologies.

As a Machine Learning Engineer, you'll design and deploy ML models to optimize ads through ad ranking, bidding, and measurement, while managing the complete ML lifecycle.

The role involves designing, building, and deploying ML models for ad ranking, bidding, and optimization, with full lifecycle ownership of ML systems.

Design and deploy production-grade ML solutions, mentor engineers, develop accelerators, optimize models, and collaborate with teams.

As an ML Solutions Architect, you'll lead ML architecture design, manage client relationships, and oversee technical execution for scalable ML solutions.

The ML Tech Lead guides ML engineering efforts, mentors engineers, sets technical directions, and contributes hands-on coding, ensuring code quality and architectural standards.

Lead a team of ML engineers and consultants to deliver AI/ML solutions on AWS while driving strategy, technical innovation, and practice development.

The Machine Learning Engineer develops and deploys models to optimize demand forecasting and vehicle positioning, collaborating with cross-functional teams to enhance rider experience.

The Machine Learning Scientist will design experiments, analyze data, develop evaluation methods, and collaborate on AI model research and production.

As a Machine Learning Scientist at LMArena, you'll lead open-source research, design experiments, and develop methodologies to evaluate AI models, collaborating across teams and engaging with the research community.

The Senior Software Engineer will lead the design of scalable, high-performance real-time data and API infrastructure, ensuring reliability and guiding engineers in best practices.

The Staff Software Engineer, AI/ML will design and develop intelligent agents, integrate them with existing systems, optimize performance, and collaborate with product teams, focusing on innovative AI technologies.

Design, build, and improve ML systems and infrastructure, mentor junior engineers, and write maintainable code in a customer-focused environment.

As a Machine Learning Engineer, you'll develop scalable ML solutions using Google Cloud Platform and Vertex AI, collaborate with teams, and operationalize models from ingestion to monitoring.

You will build frameworks for LLM-powered agents, design reinforcement learning approaches, lead development of scalable evaluation systems, and mentor other engineers while writing robust code for enterprise-grade assistants.

As a Machine Learning Support Engineer, you will address customer product issues, provide proactive guidance, and propose solutions to help clients succeed with Labelbox products.

The Senior Software Engineer II, Machine Learning will design and deploy ML algorithms, work with consumer data, and lead data teams.

The Senior Machine Learning Engineer will build and enhance AI/ML solutions for risk management, using advanced techniques like LLMs and algorithms for predictive analytics and automated assessments.

The Staff Machine Learning Engineer will develop and deploy advanced AI/ML solutions, focusing on product features like predictive analytics and risk assessments, using LLMs and classical ML techniques.

As a Machine Learning Intern at Ema, you will work on building and deploying machine learning models, analyzing datasets, and collaborating with senior engineers in a fast-paced startup environment.

Collaborate to scale self-driving systems, build training frameworks, profile model performance, and evaluate emerging technologies for training and inference.