Top Machine Learning Jobs in Vancouver

As a Sales Executive, you will hunt for new clients, manage enterprise accounts, and create revenue streams while collaborating with internal teams.

The Senior Machine Learning Ops Engineer will design and build machine learning operations infrastructure, manage ML pipelines, experiment tracking, model deployment, and collaborate with engineering teams to enhance data and ML processes.

Design and improve data pipelines for machine learning in AdTech, collaborate on data solutions, manage large data sets, and mentor junior engineers.

Design and implement high-performance auto-bidding algorithms for ad campaigns, focusing on optimization and system reliability while collaborating with cross-functional teams.

The Solutions Architect for AI/ML at Snowflake will advise clients on best practices for Data Science workloads, design solutions, and build ML pipelines. Responsibilities also include working hands-on with SQL and Python, maintaining technical expertise and collaborating with teams to improve products.

Design and optimize machine learning pipelines for large-scale systems, integrating models into user features and ensuring data integrity and performance.

Lead the design and optimization of ML systems at Scribd, managing cross-team projects, mentoring engineers, and shaping technical direction for ML initiatives.

Design and optimize machine learning systems, build scalable data pipelines, and run experiments to improve recommendations for Scribd's products.

The Staff Machine Learning Engineer will design and deploy ML models, build real-time model APIs, and collaborate across teams to drive user growth and revenue through AI/ML solutions.

Design and implement machine learning algorithms for robotic manipulation, focusing on RL and IL. Collaborate across disciplines to ensure integration and successful deployment.

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.

Develop and enhance Autodesk's AI/ML platform by designing systems, automating processes, and ensuring scalable deployment of machine learning solutions, collaborating with cross-functional teams.

As a Senior Machine Learning Engineer, you'll lead ML projects, design systems for recommendation and ranking, and collaborate cross-functionally to enhance AI insights from vast datasets.

Lead the AI/ML team to develop innovative solutions for environmental challenges, emphasizing strategic guidance, collaboration, and team empowerment.

As a Senior Machine Learning Engineer, you will build and optimize ML models, design ML infrastructure, and collaborate with teams to enhance AI products for cybersecurity.

Develop and integrate AI agents for security platforms, focusing on natural language data processing and automating security tasks.

Design, build, and deploy scalable ML solutions using GCP and Vertex AI. Collaborate with teams to operationalize models and monitor performance.

Lead an AI/ML/Data Science team to develop and deploy machine learning solutions for robotics, focusing on innovative capabilities and cost-effective cloud processing pipelines.

The Machine Learning Engineer II will develop and maintain AI/ML systems, manage cloud operations, and collaborate across teams to deploy ML-powered tools.

The Staff Machine Learning Engineer will design, develop, and deploy scalable ML algorithms, lead experimentation, and collaborate across teams to enhance AI solutions.

The Senior ML Performance Engineer will architect a Performance Testing Platform, optimize ML performance on GPUs, and validate model efficiency.

The Senior AI Engineer will develop AI features for observability tools, collaborate with cross-functional teams, and deliver scalable AI solutions.

Design and optimize machine learning and deep learning models, lead AI strategies, and ensure MLOps best practices while collaborating with various teams.

We seek Founding AI Engineers with 3+ years of experience to design and deploy ML models, optimize AI strategies, and work with startups.

The role involves developing and deploying AI/ML models, optimizing pipelines, and collaborating with startup founders on AI strategies.