AI Systems Researcher (Embedded Intelligence)

1X

Since its founding in 2015, 1X has been at the forefront of developing advanced humanoid robots designed for household use. Our mission is to create an abundant supply of labor through safe, intelligent humanoids.

We strive for excellence in all we do, solving some of the hardest problems in robotics with the world’s most talented individuals. Every part of our robots is designed and produced in house, from motor coils to AI, reflecting our vertically integrated approach. At 1X, you will own real projects, be recognized for your achievements, and be rewarded based on merit.

Our mission at 1X Labs is to provide the science and technology that enables human-level, general-purpose humanoids.

We are rigorous about identifying the gap between where humanoid performance is today and what human-level capability actually demands. From there, we go deep on fundamentals, take long but efficient and often non-obvious paths, develop new technologies, and carry those advances all the way into the product. We are uniquely positioned to make research outcomes into products with our focus and tight integration in materials, component design, systems engineering and manufacturing.

A humanoid is an unusually integrated system. Meaningful progress only emerges when sensing, actuation, materials, control, and intelligence advance together—each pushed close to its real limits. 1X Labs is built around people who have gone far enough in their own field to reason confidently at those limits, and who can engage seriously with neighboring domains because they understand which constraints truly matter.

You are deeply capable in your domain—enough that your intuition is shaped by years of work on hard, concrete problems. You don’t adopt interdisciplinarity as an identity; it’s a consequence of mastery and working on systems where no single discipline is sufficient.

You’re drawn to environments where technical depth is assumed, ideas are tested against reality, and research only counts if it ultimately ships.

As an AI Systems Researcher (Embodied Intelligence) on the 1X Labs team, your role is:

Your role is to push embodied intelligence toward human-level dexterity by working at the level where sensing, actuation, learning, and physical structure form a single closed loop.

This role exists because dexterity is not a policy problem. It is a system problem. Intelligence in a humanoid does not live in a network alone—it emerges from how perception is structured, how actions are generated and constrained, and how the body itself participates in learning. Your work targets that loop directly.

You work at the frontier of foundation models and multimodal learning, but you are not bound to existing architectures. You are expected to break with them when performance gaps demand it. You let failures in real systems—latency, instability, brittleness, lack of contact understanding—guide what models, representations, and interfaces need to exist next. Neuroscience and biological motor control are reference points, not inspiration slides.

You explicitly embrace the difference between models built for language and models that must operate in tight sensor–actuator loops. You understand that embodiment imposes constraints—bandwidth, delays, noise, compliance—that fundamentally shape how intelligence must be structured.

This role sits inside an interdisciplinary lab, embedded with hardware, sensing, biomechanics, and prototyping teams, while having direct access to 1X’s world-class AI organization. The loop between hypothesis, hardware change, experiment, and learning is intentionally short. You are expected to use that loop to unlock capabilities that cannot be reached by model-centric work alone.

You are exceptional in AI—but you are here because that excellence makes you dissatisfied. You can see the matrix: how intelligence is orchestrated across sensing, processing, and actuation, and how changing the system reshapes what learning can achieve. You want to build machines where intelligence is inseparable from the body it lives in.

Responsibilities

• Develop learning systems for embodied intelligence that operate in tight sensor–actuator loops.

• Drive progress toward human-level dexterity by addressing system-level limitations, not just model performance.

• Co-design sensing, actuation interfaces, and learning architectures with hardware and robotics teams.

• Use real-world experiments to expose performance gaps and guide architectural decisions.

• Break with existing model or control paradigms when they block progress toward physical capability.

• Translate insights from experiments into changes across models, representations, sensors, and actuation.