Top Machine Learning Jobs in Vancouver

As a Software Engineer on the AI Decisioning team, you will design and build scalable backend systems and ML infrastructure, develop AI-driven features for decision automation, and collaborate with machine learning engineers to implement innovative techniques.

As a Staff Machine Learning Engineer at Fakespot, you will apply machine learning techniques to analyze unstructured data, develop and optimize machine learning models, and collaborate with teams to enhance product features. Your focus will be on ethical AI and improving the trustworthiness of eCommerce through model deployment and monitoring.

As a Staff Machine Learning Engineer, you will lead the design and development of Generative AI solutions for Firefox, build infrastructure for model training and inference, and implement robust validation processes. You will collaborate with product management and engineering teams to enhance Firefox's AI capabilities.

The role involves developing scalable batch processing systems within the Apache Hadoop ecosystem, managing Machine Learning pipelines, and utilizing GCP for data processing. The engineer will implement DevOps best practices and collaborate effectively in a remote environment.

The Staff Data Engineer will design and implement scalable data pipelines and systems to solve complex problems involving data, machine learning, IoT, and cloud infrastructure. This role includes contributing to enterprise architecture and collaborating with engineers to propose technical solutions that integrate with ecobee’s broader systems.

The Software Developer I will design, develop, and implement software products for business projects, collaborating with teams and stakeholders. Responsibilities include coding, testing, quality assurance, and maintaining documentation while staying updated on new technologies and best practices.

As a Senior Machine Learning Engineer, you will conduct independent research, create tools for enhancing LLM security, and engage with the community. You will analyze, visualize, and interpret data while working with independent researchers to validate findings and present them at conferences.

The AI/ML and MLOps Field Engineer at Canonical will assist global companies in adopting AI using open source technologies on cloud infrastructures, primarily focusing on Linux and Kubernetes. Responsibilities include architecting cloud solutions, engaging in customer interactions, and solving complex data architecture problems using various data technologies.