AI Research Engineer/Scientist - Human Data - Robotics

Flexion Robotics; Altburg; Vor Ort; CHF 150.000 - 210.000; Vollzeit

Benefits dieser Stelle

Enhanced pension plan

Enhanced holiday & paid leave perks

Central Zürich office

Zusammenfassung

Flexion Robotics is seeking an AI Research Engineer/Scientist specializing in human data and robotics to advance foundation models and dexterous manipulation. You will work with video demonstrations, wearable capture systems, and other data streams to scale robotic perception and control from lab to real-world environments.

The role emphasizes end-to-end lifecycle, from data capture to model deployment on humanoid platforms, with a focus on scalable experiments and robust, practical

Qualifikationen

• PhD in Computer Science or related field or equivalent practical experience.
• Experience with vision, vision-language, video, and other multimodal models, especially with human data.
• Experience with multimodal generative modeling, training, and inference.
• Experience with reinforcement learning and imitation learning.

Aufgaben

• Scalable Human Data Integration: Develop methodologies and capture pipelines to integrate human video demonstrations, wearable systems, and unconstrained manipulation data directly into foundation model and RL workflows.
• 3D Object & Interaction Reconstruction: Build automated pipelines to reconstruct manipulated 3D objects and environments from capture data, importing digital twin assets into simulation to enable scalable scenario synthesis.
• Simulation-to-Real & Reinforcement Learning: Build simulation environments with reconstructed assets, leveraging reinforcement learning, tactile, and force feedback to produce dexterous manipulation policies.
• Multimodal Policy Architecture & Evaluation: Design, train, and evaluate robot foundation models that translate multi-sensor data streams into robust control.
• Embodied Transfer: Design algorithms to bridge human embodiment to high-DOF dexterous hands and humanoid platforms.

Kenntnisse

Multimodal models

Reinforcement learning

Imitation learning

Data curation

Ausbildung

PhD in Computer Science

Tools

Simulation environments

Jobbeschreibung

AI Research Engineer/Scientist - Human Data - Robotics

Data & ML

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AI Research Engineer/Scientist - Human Data - Robotics

At Flexion, we're building the intelligence layer powering the next generation of humanoid robots. Our mission is to accelerate the transition from fragile prototypes to real-world humanoid deployment. We are founded by leading scientists in robot reinforcement learning (ex-Nvidia, ex-ETH Zürich), and backed by leading international VC firms. In just months, we’ve gone from our first line of code to deploying real humanoid capabilities.

The role

We are seeking an expert in robotics foundation models and multi-modal human action data to advance the frontiers of generalizable manipulation. This position bridges the gap between human embodiment and robotic execution by leveraging video demonstrations, wearable capture systems (such as UMI or sensorized gloves), and complementary data sources. You bring a deep understanding of the full lifecycle required to scale dexterous capabilities, spanning the design and deployment of specialized capture devices, dataset curation, and algorithmic and architectural modeling.

As a Research Scientist/Engineer, you will drive large-scale experimentation and deploy breakthrough ideas across core physical intelligence problems. You will own the development of novel systems that turn cutting-edge research into robust, real-world implementations, ultimately pushing the limits of what our hardware can achieve.

Key responsibilities

Scalable Human Data Integration: Develop methodologies and capture pipelines to integrate human video demonstrations, wearable systems (such as UMI or sensorized gloves), and unconstrained manipulation data directly into foundation model and RL workflows.

3D Object & Interaction Reconstruction: Build automated pipelines to reconstruct manipulated 3D objects and environments from capture data, importing digital twin assets into simulation to enable scalable scenario synthesis.

Simulation-to-Real & Reinforcement Learning: Build simulation environments with reconstructed assets, leveraging reinforcement learning, tactile, and force feedback to produce dexterous manipulation policies.

Multimodal Policy Architecture & Evaluation: Design, train, and evaluate robot foundation models that translate multi-sensor data streams into robust control.

Embodied Transfer: Design algorithms to bridge human embodiment to high-DOF dexterous hands and humanoid platforms.

Requirements

Requirements

PhD in Computer Science, a related field, or equivalent practical experience.

Experience with vision, vision-language, video, and other multimodal models, especially ones trained with human data.

Experience with multimodal generative modeling, training, and inference.

Experience with reinforcement learning and imitation learning.

Preferred qualifications:

Experience with capture methodologies, dataset design, experimentation, and incorporation of captured human action data into VLA, WAM, or RL training.

Experience with simulators and real-world robots, especially dexterous manipulation, as well as multimodal sensing (e.g., tactile, forces).

Competitive compensation

Enhanced pension plan

Enhanced holiday & paid leave perks

Central Zürich office with top-tier robotics testing facilities and infrastructure

Joining Europe's leading robotics team & exposure to never-done-before research

Energetic, collaborative culture with a bias for action and regular community events

Competitive Compensation

Joining a leading robotics team & exposure to never-done-before research

Energetic, collaborative culture with a bias for action and regular community events

Enhanced pension plan

Enhanced holiday & paid leave perks

Central Zürich office with top-tier robotics testing facilities and infrastructure

401(k) with company contributions

Health, dental & vision coverage with the flexibility to choose your own plan

Shape the Future