Principal AI Research Engineer - World Models

Reposted One Month Ago
Be an Early Applicant
2 Locations
In-Office
Senior level
Robotics
The Role
Lead the design and training of large-scale video/world models for robotics. Develop controllable simulators and evaluate policy success. Contribute to building a flagbearer robotics company with a focus on high success rates in real-world applications.
Summary Generated by Built In

Company Overview

Reflex Robotics builds general-purpose, AI-powered humanoid robots for the toughest jobs in industry.

We’re focused on jobs that are genuinely hard on the human body: lifting 40-pound bags of dog food, loading boxes for an entire shift, and moving heavy materials from floor to high overhead shelves. Not just lightweight tasks in controlled environments. Actual, back-breaking work.

Factory and warehouse work demands more. The hardware needs strength, reach, precision, speed, and the battery life to be useful across multiple shifts. It also needs to deliver a clear return today, not in some hypothetical future. Our robot costs $32K at development volumes today.

We build the full robot stack ourselves, from cameras and compute to actuators, electronics, and software. Our custom-built supervision stack helps handle the hard parts of deployment, from real floor variability to keeping work moving without line disruption. That supervision also generates proprietary real-world data that helps improve autonomy over time.

We are a four year old startup backed by Khosla Ventures and a team of other great investors. Our team includes alumni from Anduril, Oculus, Amazon, Waymo, Skydio, Boston Dynamics, ASML, MIT, Jane Street, and Joby Aviation.

 


Key Company Beliefs

  • We are obsessed with shipping robots.

  • A humanoid robot is only valuable if it solves a real customer problem. Cool demos are fun, but reliable work is what matters.

  • Low cost is what makes widespread deployment possible.

  • High-quality, proprietary robotics data is the foundation of the next generation of physical AI.

  • Getting nerd-sniped by an engineering metric is way less important than solving our customers’ biggest pain points.


What We’re Looking For

We’re still a small team—which means high ownership, high equity, and the chance to shape the product from the ground up.

VLAs and other great “base policies” for robotics achieve ~80% success rates, but in real robot deployments, it’s essential to achieve 99.99% success rates. We can’t ask our customers to tolerate our robots packing three socks into a bin instead of four, or swapping shipping labels between two packages—not even once!
You should apply for this role if:

  • You’ve architected and trained large-scale video/world models (ex. Sora, Veo)

  • You’ve turned generative models into controllable simulators: action‑/state‑conditioned rollouts

  • You’ve built the data & eval stack for world modeling to quantify downstream policy success

You’d be joining a company that already has a solid core business—with working hardware, delighted customers, and profitable unit economics. Reflex is de-risked enough to see the hazy outlines of success, but still small enough that there’s enormous upside up for grabs.


Come Join Us

This is a rare opportunity to help build a flagship robotics company from the ground up—and to do work that will truly matter, reshaping what people believe is possible in robotics.

We love to see the things you’ve worked on. Have a portfolio or insane project you’ve worked on? Share it. We’re looking for people who push past the status quo, are passionate at work and in their own time—we’re looking for people who want to win.

Skills Required

  • Experience architecting large-scale video/world models
  • Ability to turn generative models into controllable simulators
  • Experience building data and evaluation stacks for world modeling
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The Company
HQ: New York, New York
19 Employees
Year Founded: 2022

What We Do

We're building affordable general-purpose robots to free humanity from the drudgery of boring and repetitive tasks

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