Top Machine Learning Jobs in Vancouver

As a Senior/Principal Machine Learning Engineer, you will design and build core ML systems for Workday's AI agents, owning the entire lifecycle from problem framing to deployment and improvement, while collaborating cross-functionally to create scalable solutions.

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 Senior Software Engineer II in Machine Learning, you'll design and implement AI systems, focusing on production-grade ML techniques, collaborating with cross-functional teams, and ensuring systems are reliable and maintainable.

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

As a Machine Learning Engineer, you will develop user experiences using LLMs and predictive analysis, deliver ML solutions, and ensure continuous improvement in AI products at scale.

As an Account Executive, you will drive new business opportunities and manage existing accounts in the telecom sector, contributing to revenue growth and sales strategy execution.

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

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

As a Senior Machine Learning Engineer, you will design and train ML models for logistics, manage their production deployment, and optimize their performance while collaborating with the data science team.

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.

As a Software Engineering Intern, you'll develop features for user-facing products, work on API platforms, and design data pipelines while gaining hands-on experience in AI technologies.

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.

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

The Data Scientist will solve real-world problems utilizing data science techniques and build end-to-end data pipelines, collaborating with multiple teams to deliver solutions.

Design and manage evaluation datasets, develop evaluation pipelines, score assistant quality using LLMs, and build observability for AI agents.

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

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.

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

The role involves building deep learning models for ad candidate retrieval and ranking, improving recommendation systems, and taking ownership of ML systems.

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.

Design, build, and optimize large-scale cloud data ingestion, preprocessing, distributed training, and benchmarking infrastructure for geospatial foundation models. Contribute to model architecture, fine-tuning for agriculture, ML experiment tooling, and maintain documentation while working in an Agile team.

Design and deploy ML solutions for video analytics. Build MLOps pipelines, collaborate on product features, and troubleshoot AI/ML issues.

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.