Antioch, New York or San Francisco (in-person)
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.
You'll work alongside Antioch's founders, simulation engineers developing physics and sensor models, platform engineers building cloud infrastructure and developer tools, and technical artists creating simulation worlds.
WHO ARE WE?
Antioch is the simulation platform for robotics and autonomy. We allow teams to develop, evaluate, and generate synthetic data for their physical systems in high-fidelity cloud simulation, accelerated by 3D-native agents.
With Antioch, teams create precision-calibrated digital twins, generate testing environments, and run massively parallel simulation scenarios. By moving development out of the field and into software, Antioch drastically reduces dependence on expensive, slow, and incomplete real-world testing.
We work with leading robotics, autonomy, and perception teams to make the deployment of physical autonomous systems safer, faster, and more cost-effective.
WHO ARE WE LOOKING FOR?
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Source: the Antioch Ashby job board. We last checked this job 2 h ago. We first saw it 8 days ago. A job on a job board does not always mean that the team interviews people now. We found this job board in a public list. We did not yet compare it with the careers page of the company.
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