Member of Technical Staff, Machine Learning

We're hiring a Member of Technical Staff, Machine Learning to be a core contributor to Antioch's ML team. You'll build the methods that make our simulations faithful to physical systems, and help drive the evolution from classical to learned simulation.

This is a hands-on technical role. You'll spend your time writing code, developing models, designing experiments, and shipping production capabilities alongside our simulation and core platform teams.

The central challenge is making simulation a reliable guide to real-world decisions. You'll combine physical models with learning from real data, demonstrate when simulated improvements transfer to hardware, and build a data feedback loop in which each deployment improves our models and calibration methods. You'll also contribute to Antioch's longer-term approach to learned simulation, including world models and diffusion models, grounded in measurable customer outcomes.

If you like the 0 → 1 grind and want your work to directly determine whether autonomous systems succeed in the real world, you'll fit right in.