Top Machine Learning Jobs in Vancouver

Design, develop, and deploy advanced machine learning models for generative tasks, working collaboratively in a team to implement cutting-edge AI solutions.

Lead technical initiatives for machine learning features, build scalable ETL pipelines, deploy production services, and collaborate with cross-functional teams.

The QA Engineering Lead will oversee quality assurance processes, mentor the QA team, and implement best practices to ensure high-quality software delivery.

The Senior Software Engineer will discuss and research features, write code and documentation, and engage with the community on platforms like GitHub and Discord. Strong Python skills and excellent communication are essential.

Design and implement machine learning models to mitigate fraud and risks, ensuring compliance and working closely with cross-functional teams.

Develop software to integrate machine learning into Workday's platform, design interfaces, and improve user feedback collection. Collaborate with integration teams for seamless ML application.

The Full Stack Engineer will develop and maintain AI/ML applications, collaborate with teams for integration, optimize performance, and contribute to architecture and strategy.

As a Machine Learning Engineer at Workday, you will develop AI agents and frameworks, collaborating with teams to enhance product functionalities through advanced machine learning techniques.

The Machine Learning Engineer will develop algorithms and models for data analysis, collaborating with teams to enhance app insights and performance.

The Associate, ML Engagement Management will oversee program execution phases, design and document requirements, build customer relationships, and ensure project success.

Develop and productionize end-to-end neural networks for autonomous driving. Collaborate with teams to scale and deploy ML models, ensuring engineering excellence.

As a Senior Machine Learning Engineer, you will build MLOps pipelines, integrate cloud technologies, manage data workflows, and optimize model deployment, collaborating across teams to innovate and enhance AI products.

The Machine Learning Engineer will develop and deploy ML methods for 3D spatial understanding, collaborating with research and production teams.

Design and implement secure, scalable ML infrastructure and workflows. Manage CI/CD pipelines, collaborate with data scientists, and maintain documentation for regulatory compliance.

Design and evaluate machine learning models focusing on label noise, unsupervised learning, and build analytics solutions in collaboration with cross-functional teams.

As a Full Stack Engineer on the AI Decisioning team, you will develop intuitive interfaces for non-technical users, integrating ML models and offering insights to enhance marketing strategies. You will collaborate with cross-functional teams to architect and build robust marketing products.

The role involves designing experimental frameworks for LLM performance evaluation, implementing automated pipelines, and collaborating on model integration and analysis within a fast-paced ML environment.