Website Liminal Insights

As a machine learning engineer at Liminal you will join a small, nimble team of engineers creating cutting-edge battery inspection equipment. You will be an integral part of developing models with the data produced by this equipment, developing a deeper understanding of the data’s relationship to the battery’s production history and performance, and creating tools and techniques to deploy, track, and monitor the performance of our models.

On a typical day, you may: design and implement algorithms for distilling ultrasonic signals into meaningful features, and correlate those features with performance data; deploy new models and algorithms into production; manage the tracking and performance of our model offerings with customers; build analytics tools and visualizations to empower our engineers and customers; optimize, automate, and streamline our analytics pipeline, and integrate the pipeline with real-time data streams; or communicate your work to stakeholders with varied backgrounds.

You value careful listening, thoughtful questions, and data-driven discussions. You are comfortable with gathering and distilling information to drive the direction of open-ended projects. The ideal candidate will approach this work with a mixture of intellectual curiosity, thoughtful creativity, and methodical rigor. The ideal candidate gets great satisfaction from seeing people do great things with their work, and above all is excited to solve hard problems that have a positive impact on the world’s clean energy future.

To apply for this job please visit apply.workable.com.