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Lili-o produit des données d’entraînement et des logiciels pour les robots autonomes opérant dans des environnements domestiques. Ses clients sont des entreprises et laboratoires de recherche en robotique, qui cherchent à entraîner des robots aux variations du monde réel.

Repères sur Lili-o
Secteur
Logiciels et Internet
Type d’entreprise
Financée par du capital-risque
Stade
Startup early-stage
Domaine officiel
lili-o.com
Création
2025 · 1 an
Dernière levée
Seed · 2026-06-01
Offres ouvertes
3

Investisseurs mentionnés

Détails de l’offre

La description complète publiée par Lili-o.

Voir l’offre originale ↗

Description de l’offre

About Lili-O

Our mission

is to empower every person with a robot

  • whether that's an elderly person who needs a hand at home or a young professional who wants their time back. To get there, we're building the brain that lets robots automate specific long-horizon tasks in unstructured, real-world environments. That brain combines skill learning, vision, and long-horizon planning
  • but none of it matters if the robot's body can't move reliably, precisely, and safely. That's where this role comes in.

The Role

As a Control / Motion Engineer, you'll own and optimize our control stack — from whole-body control down to real-time deployment on hardware. You'll work closely with the mechatronics team, since control performance is inseparable from the robot's mechanical design. This is primarily an engineering role: building, testing, and hardening the control systems that everything else runs on, while staying hardware-agnostic so our stack can move to new platforms.

Responsibilities

Optimize and harden the existing control stack (IK, MPC, low-level control) Develop a Whole Body Controller (WBC), and/or evaluate and integrate existing WBC solutions

  • Deploy and validate R&D control algorithms on real robots
  • Manage and maintain URDF models, keeping the control stack hardware-agnostic across platforms
  • Work closely with the mechatronics team on actuator behavior, CAN communication, and hardware integration
  • Deploy and optimize control code on embedded targets (e.g. Jetson)
  • Participate in QA: testing, validating, and debugging control behavior on real hardware before and after releases

What We're Looking For

Hard Skills Whole Body Control (WBC) Inverse Kinematics (IK) and Model Predictive Control (MPC) Experience with cuRobot and/or Placo (or equivalent motion planning/control libraries) CAN bus communication with hardware Strong C++ skills for real-time control code Experience deploying on embedded platforms (e.g. NVIDIA Jetson) Comfort with URDF and keeping control software hardware-agnostic Background Engineering degree or equivalent experience in robotics, mechatronics, or controls Hands-on experience taking control algorithms from simulation to real hardware Experience working alongside

mechanical/mechatronics teams, understanding how hardware constraints shape control design Soft Skills Hands-on, pragmatic engineering mindset

  • comfortable debugging on real hardware, not just in simulation Close collaboration with mechatronics, R&D, and QA Attention to detail and reliability
  • this stack runs everything else Practical Information Location: Paris Contract type: Full-time Work Culture
  • What to Expect

This role is for someone who thrives with autonomy and ambiguity, not someone who needs a roadmap handed to them every morning.

You'll often work independently. Long stretches of focused, self-directed engineering work, with limited day-to-day supervision. We trust you to figure out the path forward.

Travel is part of the job. Conferences, labs, partner visits — if there's a relevant event abroad, we expect you to be comfortable hopping on a plane to represent Lili-O and bring ideas back.

Priorities shift, fast. This is a startup. We will sometimes change direction and de-prioritize work you've put real effort into. It's never personal — it's how startups survive.

Comfort with uncertainty. Specs, scope, and even the problem definition will evolve. You'll be expected to bring structure to that ambiguity rather than wait for it to be resolved for you.

If you get energy from solving open problems, adapting on the fly, and owning your slice of the robot end-to-end — let's talk.