Machine Learning Engineer

Required

• Experience: 2 to 6 years of software engineering with a focus on machine learning and/or computer vision. We want someone with true end-to-end experience: you've taken models from raw data to production and owned what happens after they ship.
• Both Sides: Strong software engineering fundamentals plus hands-on ML. You write production-quality code and you train and debug models. The two overlap, and we want someone comfortable across both.
• Full Lifecycle: You've owned models beyond the notebook: trained, deployed, monitored, and iterated in production.
• Real CV depth. Experience with modern computer vision and the judgment to know when a classical technique beats a heavy model. You're not reaching for a transformer when a filter will do.
• We're a small team, which means a more deliberate interview process than you might be used to. In exchange, you get real autonomy from day one, direct access to the people setting technical direction, and work that ships to real roads in weeks, not quarters.
• The Process: We hire software engineers in cohorts. Rather than evaluate candidates on a rolling basis, we collect applications over a two-week window and assess everyone together. This allows us to make fair, considered comparisons and move the strongest candidates through the process efficiently and fairly.
• The process has five stages:
• Application Review: We (a human) read every application carefully at the close of the approximately two-week window.
• Ezra: A brief AI-assisted screening to make sure we're a mutual fit before investing more of your time. Think of this as a way to augment your application.
• Screening Interview: A focused conversation to understand your background and motivations.
• Technical Interview: A deeper evaluation of your skills and how you think through problems.
• Experience Interview: A conversation about how you've worked and what you've built.