Top Machine Learning Jobs in Vancouver

The role involves leading AI/ML technical planning, evaluating new technologies, collaborating with stakeholders, and fostering innovation in the team.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

Lead the design and development of software for quantum machine learning methods. Collaborate with researchers and communicate findings. Oversee best practices in machine learning systems and influence product offerings.

As a Software Engineer in ML Infrastructure, you will develop scalable data pipelines, enhance data discovery, and collaborate with teams on data organization and ML features.

We seek a Machine Learning Engineer to develop, deploy, and optimize advanced ML systems, focusing on AI Agent evaluation and optimization across complex environments.

As a Machine Learning Engineer, you will develop and optimize AI models and systems, focusing on Information Retrieval and Natural Language Processing while working with exclusive datasets to deliver valuable solutions for customers.

The role involves designing, developing, and deploying scalable machine learning models and AI systems, focusing on end-to-end ownership of the ML lifecycle, collaborating cross-functionally, advocating for technical excellence, and mentoring junior engineers while championing Responsible AI practices.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

The Product Manager Insurer Experience will enhance the Insurer experience on the AI Risk Exchange platform by identifying opportunities, collaborating with teams, and delivering high-impact solutions that drive value for third-party insurers.

Lead research, design, and implementation of large-scale cloud data ingestion, preprocessing, distributed training, and benchmarking for geospatial foundation models focused on agriculture. Contribute to model architecture, fine-tuning, tooling, documentation, and Agile development processes.

As an ML Engineer at Luma AI, you will design high-performance model serving pipelines, manage GPU resources, and optimize CI/CD for large-scale AI systems.

The role involves designing scalable data pipelines for 3D, video, and sensor data, optimizing infrastructure, and productionizing ML models with researchers.

Design and deploy production ML models for pricing decisions at Lime, collaborating with engineers, mentoring teams, and influencing strategy.

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.

The Principal Risk Quality Engineer leads the Risk Management process for AI/ML medical technology, ensuring safety, compliance, and risk assessment throughout the product lifecycle.

Develop and optimize auto-labelling systems using ML and computer vision, manage data pipelines, and collaborate with researchers.

Responsible for developing and deploying AI/ML models, integrating systems, optimizing LLM performance, and implementing MLOps practices within GCP.

The role involves improving machine learning ranking models, implementing algorithms, and taking full ownership of machine learning systems within Quora's product.

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

The ML Ops role focuses on building and managing infrastructure for deploying AI models in production, ensuring scalability, performance, and reliability. Key responsibilities include optimizing GPU workloads, designing CI/CD pipelines, and implementing observability for their platform.

Build scalable ML data pipelines for Waabi's autonomous driving platform. Design, optimize, and manage datasets and training processes while collaborating with scientists and engineers.

Design and deploy machine learning systems for autonomous vehicles, collaborating with teams to improve model performance and safety using real-world data.

As a Senior Machine Learning Engineer, you will develop and optimize ML solutions, ensure efficient data flow, and lead project discussions with clients.

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.

The role involves architecting Agentic AI products, driving optimization algorithms, developing AI frameworks, and managing the full ML lifecycle while collaborating with cross-functional teams.