Top AI Jobs in Vancouver

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.

As a Senior Backend Engineer on the Conversations AI team, you will architect and maintain scalable APIs for AI-driven conversational tools, integrating LLMs and OpenAI models. Your work will enhance customer engagement via SMS and contribute to the success of ecommerce brands. You will also mentor junior engineers and lead projects focusing on technical excellence and business value.

The job involves providing coding expertise to assist in training AI models by crafting questions, evaluating code generated by AI, and ensuring attention to detail. Candidates are expected to work flexibly and remotely, contributing to innovative projects.

The Senior AI Engineer will build applications focusing on GenAI solutions, working collaboratively with a distributed team. Responsibilities include implementing innovative AI applications, conducting code reviews, ensuring communication and quality standards, and refining the GenAI strategy while navigating ambiguity in a growing startup.

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.

The AI Solutions Consultant will work closely with the sales team, guiding clients on utilizing AI Decisioning effectively, and developing technical content. Responsibilities include understanding customer pain points, executing technical projects, and advocating for customer needs within the company.

The Software Engineer will be responsible for developing large new areas within data management software, handling the entire product lifecycle, and ensuring high reliability of system software. This role demands experience with AI infrastructure at scale and solid Python knowledge. Multi-tasking and quick adaptation to new technologies are essential.