Elevate your career at RBC Borealis as a Machine Learning Platform Engineer. Contribute your expertise in ML infrastructure, automation tools, and collaborative solutions in a supportive environment. In this full time position, you will play a pivotal role in designing and implementing machine learning systems within a passionate team.
Your focus will include developing MLOps tools and optimizing deployment processes while collaborating with engineers and researchers on creative projects. This role will leverage your extensive experience in cloud and on-premise environments as you support critical infrastructure decisions. Key Responsibilities:
Design and optimize machine learning deployment tools
Implement standards for data and ML pipelines
Collaborate on automating code analysis and deployments
Support applications with infrastructure design choices
Build scalable cloud and on-premise ML systems Requirements:
5+ years in distributed systems and Machine Learning
Experience with DevOps pipelines like Jenkins and GitHub
Familiarity with MLOps tools such as AirFlow and KubeFlow
Solid coding skills in Python and Bash
Knowledge of monitoring solutions and best practices Join RBC Borealis to shape the future of finance through machine learning and innovation.