Machine Learning Engineer

If you want to move beyond coursework into real machine learning systems, this is a solid entry point. You'll work on risk engineering technology that actually gets used across a global organization. That's the kind of early-career project that builds your portfolio and your credibility.

The role centers on delivering machine learning-based systems and contributing to the technical architecture and strategy of risk technology initiatives. You'll be part of a team building cloud-native solutions, which means exposure to modern infrastructure and real-world engineering practices from day one.

This fits you if you have a foundation in ML or data science—through coursework, projects, or personal work. Computer science, mathematics, engineering, or related majors are typical backgrounds. You don't need years of experience, but you should be comfortable reading code, understanding systems thinking, and learning in a professional setting. A GitHub profile or project portfolio helps.

To apply, visit CareerJumpShip and submit your résumé and a link to your work. Note that this position does not offer visa sponsorship at this time.