Applied ML Engineer - Model R&D

Responsibilities:

• Take research-quality and prototype ML code from the R&D team and refactor it into production-ready, maintainable, deployable systems — closing the gap between 'it works' and 'it runs reliably at scale.'
• Own end-to-end deployment of ML pipelines: data ingestion, feature engineering, model serving, monitoring, and reliability.
• Integrate structured development practices — task management (Jira/Linear), Git workflows, code reviews, CI/CD — on a team that moves fast and needs the discipline to match.

About you:

• You came up in a real code shop — a structured, team-based engineering environment where architecture decisions were debated, code reviews were rigorous, and task management was just how work got done.
• You are a builder first. Research is interesting to you, but shipping is what gets you up in the morning. You take messy, promising work and make it production-grade — and you take pride in that.
• You are collaborative by nature. You've worked alongside strong engineers, shared ownership of systems, and given and received hard feedback on code.

What we offer:

• The opportunity to learn, experiment and build in an entrepreneurial environment.
• Remote-first, distributed team with frequent in-person sprints and retreats.
• Competitive total comp with strong bonus upside tied to performance.