Top Machine Learning Jobs in Vancouver

The job focuses on expanding teams in Protein Science, Drug Development, Manufacturing, Quality, and supporting roles in various scientific and engineering fields.

The Director of Product for Data Flywheel will lead the roadmap for data initiatives, ensuring quality and compliance across various engineering teams and initiatives. Responsibilities include managing data metrics, supporting data pipelines, and collaborating across teams to enhance infrastructure.

Develop and enhance machine learning systems for fraud detection, build pipelines, prototype models, ensure model health, and collaborate with cross-functional teams.

The Senior Staff Machine Learning Engineer will lead the design and scaling of advanced ML systems, mentor engineers, and define technical strategy across Affirm.

Lead engineering to build a unified platform for agent interactions with Workday Data Cloud, managing teams, and ensuring high-quality software delivery.

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

The AI Research Engineer will design, implement, and improve AI systems for therapy, enhance evaluation methods, and collaborate with various teams to innovate and ensure safety in AI therapy.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions on-site, collaborating with engineering teams to operationalize AI systems across multi-cloud platforms.

The VP of Data & AI Engineering leads Duck Creek's enterprise data and AI strategy, overseeing global teams, implementing scalable platforms, and ensuring data governance and responsible AI practices.

Lead a product portfolio for Clio's core case management experience, utilizing legal expertise to drive innovation and user adoption while simplifying attorney workflows with AI tools.

Lead Growth Product strategy and execution to drive customer acquisition, onboarding, and GTM efficiency. Manage a team of product managers, define measurable goals, collaborate with Engineering, Design, Marketing, Sales and Data, and build scalable systems (account scoring, TAM data, outbound automation, ML models) to improve pipeline conversion, CAC payback, and activation outcomes.

Develop and scale machine learning training systems for robotics data, optimize training pipelines, and collaborate with ML researchers to enhance autonomy models.

Manage technical programs for generative AI video models, translating research into milestones, coordinating teams, and ensuring successful execution across all phases.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

Lead the data and ML product vision: define roadmap, prototype models on noisy behavioral datasets, translate signals into user-facing features, partner with engineering to productionize ML, and generate insights to inform product roadmaps.

The Junior Data Scientist will design and develop data models using Machine Learning and Analytics for trading and compliance in finance.

Lead the product vision for innovative AI technologies, translating research into marketable products, and collaborating with cross-functional teams.

As Senior Product Manager, you'll lead AI innovation in financial advisory tools, collaborating with teams to enhance user experiences and product impact.

Seeking a Research Scientist to develop AI models for enhancing 3D reconstruction processes, requiring strong skills in computer vision and neural reconstructions.

The Applied Scientist will transform raw data into actionable insights by developing machine learning models for personalization, ranking, and optimization to enhance conversion and revenue. This role emphasizes building production systems, frameworks for experimentation, and communication with team members regarding technical challenges.

Lead development and execution of a multi-year automation and AI/Industry 4.0 roadmap for manufacturing. Build and mentor a multidisciplinary automation team, oversee end-to-end program delivery (concept through commissioning), integrate ML/vision/IoT/SCADA systems, manage budget and metrics, and drive measurable improvements in safety, quality, throughput, and cost.

Embed with clients to gather requirements and design AI-driven solutions for fraud and fincrime. Architect, train, evaluate, and deploy custom AI agents and workflows, optimize model performance, establish risk metrics and evaluation pipelines, and collaborate with engineering/product teams to scale into production.

Lead and mentor a multidisciplinary UX/Product Design team to create strategy-driven, visually excellent experiences across owned and third-party platforms. Integrate AI and machine learning into UX, design conversational/agent interfaces, run workshops, manage high-visibility client projects, recruit and grow the team, and represent the agency externally.

In this role, you will lead AI personalization initiatives, develop AI/ML models for user experience, collaborate across teams, and ensure rigorous development practices.

The Solutions Engineer will engage with stakeholders to design AI-powered engineering solutions, bridging business needs and technical execution while guiding customers through AI integration.