Top Machine Learning Jobs in Vancouver

The Technical Product Manager will lead product direction, interface with engineering teams, and ensure the successful deployment of AI-powered safety systems. Responsibilities include defining product vision, translating customer needs, and maintaining high product quality.

The Account Executive will drive sales, develop strategies for business growth, manage accounts, and lead collaborations with clients and teams in the insurance sector.

Lead Machine Learning Engineer responsible for setting technical vision, guiding teams, architecting solutions, and overseeing project delivery on Google Cloud. Requires strong ML fundamentals and excellent communication skills.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

The role involves improving recommendation systems using machine learning, developing end-to-end ML systems, and collaborating with engineers.

The Senior Machine Learning Engineer will develop and optimize AI image generation models, monitor production issues, and collaborate on ML solutions for generative features.

The Staff ML Research Scientist will pioneer deep learning architectures for drug discovery, driving technical strategy and mentoring junior researchers.

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

Lead the design and optimization of programmatic bidding systems, collaborating with engineers and applying analytical methodologies to enhance performance.

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.

Design and build scalable .NET backend services and gRPC microservices; optimize data layers (SQL Server, MongoDB, Elasticsearch); implement cloud integrations on AWS and Azure; ship AI/ML features (LLMs, RAG, vector search, ranking, personalization) and operate MCP servers; contribute to CI/CD, observability, containerization, and production ML integrations impacting high-traffic consumer marketplaces.

Build and automate large-scale ML data pipelines and tooling for autonomous trucking. Improve dataset curation, deduplication, labeling, evaluation, and metrics infrastructure. Collaborate with robotics, autonomy, and infra teams to support continuous learning, deployment, and scalable AI infrastructure for Kodiak's fleet.

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.

As a Senior Machine Learning Engineer, you will own the ML stack, develop generation systems, improve quality, collaborate cross-functionally, and build data pipelines.

The Head of AI will define and execute an AI roadmap, lead research initiatives, mentor the AI team, and collaborate with senior leadership to enhance health technology.

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

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.

The Senior Software Engineer will develop AI/ML features, build robust APIs, create user-friendly UIs, and integrate AI models into ClickHouse Cloud.

The Senior MLOps Engineer will build and operate scalable infrastructure for AI solutions, collaborating on ML-driven features, troubleshooting production issues, and mentoring team members.

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.

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.

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.

As a Senior Machine Learning Engineer, you will create machine learning solutions, optimize models, and lead client projects using cloud technologies.

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

The role involves collaborating with customers to solve engineering challenges using machine learning, develop solutions, train teams, and improve products based on feedback.