Research Engineer/Scientist - Dexterous Manipulation

Flexion; Zürich; On-site; CHF 150,000 - 230,000; Full time

Benefits offered by this job

Competitive compensation

Enhanced pension plan

Enhanced holiday & paid leave perks

Relocation & permit sponsorship

Central Zürich office with robotics测试

Job summary

Flexion in Zürich is hiring an AI Research Engineer to lead dexterous manipulation through egocentric video-based Foundation Models. You will build VLA models that translate observed human actions into 20+ DoF robot policies and deploy controllers on real hardware in unstructured settings.

The role emphasizes large-scale pre-training, multi-modal integration, and offline RL with simulation for robust robotic manipulation. Collaboration across AI engineering is essential.

Qualifications

• PhD or Master’s degree in Robotics, ML, or closely related field with a focus on data-driven manipulation, egocentric vision, or foundation models.
• Experience with Humanoid or Dexterous Manipulation, including a deep understanding of contact-rich physics.
• Excellent knowledge of Python, PyTorch, and distributed training of large-scale neural networks (FSDP, NCCL).
• Proven expertise in Diffusion Models, Flow Matching, and Transformers.
• Hands-on experience deploying learning-based controllers on real robot hardware.
• Experience with Reinforcement Learning and simulation environments (e.g., IsaacLab, MuJoCo)

Responsibilities

• Architect and implement large-scale pre-training objectives for egocentric video datasets to learn generalizable representations of hand-object interactions and spatial-temporal dynamics.
• Develop and scale multi-modal Foundation Models that unify visual perception and natural language instructions into actionable robotic trajectories.
• Design and optimize generative action heads using Diffusion Models and Flow-matching techniques to capture the multi-modal distribution of complex human movements.
• Develop novel algorithms to align human-centric video representations with the kinematic constraints of 20+ DoF humanoid systems.
• Utilize Offline RL and high-fidelity simulation fine-tuning to optimize foundation model performance for high-success-rate physical manipulation.
• Translate cutting-edge research in scaling laws and world models into production-ready architectures that enhance robot reliability and autonomy.

Skills

Python

PyTorch

Distributed training

Reinforcement Learning

Simulation environments

Education

PhD or Master’s in Robotics or Machine Learning

Tools

Diffusion Models

Flow Matching

Transformers

NCCL

FSDP

Job description

AI Research Engineer - Dexterous Manipulation (Egocentric Models)

Location: Zürich, Switzerland

Department: AI Engineering

Description

About Flexion

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 dexterous manipulation and large-scale modeling to lead the development of our physical foundation models. The goal of this position is to leverage internet-scale egocentric video to build Vision-Language-Action (VLA) models that enable our humanoid robots to interact with the world with human-like fluidity. You bring a deep understanding of how to bridge the gap between observing human actions in video and executing high-DOF (20+) motor control.

As a Research Engineer for Dexterous Manipulation at Flexion, you’ll work in our Zürich office to develop and deploy state-of-the-art learning-based controllers. You will take ownership of the model architecture, integrating egocentric priors with real-time robot policies, to ensure our hardware can manipulate objects reliably and flexibly in unstructured environments.

Key Responsibilities

• Scalable Egocentric Pre-training: Architect and implement large-scale pre-training objectives for egocentric video datasets to learn generalizable representations of hand-object interactions and spatial-temporal dynamics.
• VLA Foundation Modeling: Develop and scale multi-modal Foundation Models that unify visual perception and natural language instructions into actionable robotic trajectories.
• Generative Policy Design: Design and optimize generative action heads using Diffusion Models and Flow-matching techniques to capture the multi-modal distribution of complex human movements.
• Humanoid Motion Alignment: Develop novel algorithms to align human-centric video representations with the kinematic constraints of 20+ DoF humanoid systems, ensuring fluid and stable execution.
• Reinforcement Learning & Fine-tuning: Utilize Offline RL and high-fidelity simulation fine-tuning to optimize foundation model performance for high-success-rate physical manipulation.
• Cross-Functional Research: Translate cutting-edge research in scaling laws and world models into production-ready architectures that enhance robot reliability and autonomy.

Requirements

• PhD or Master’s degree in Robotics, Machine Learning, or a closely related field, with a strong focus on data-driven manipulation, egocentric vision, or foundation models.
• Experience with Humanoid or Dexterous Manipulation, including a deep understanding of contact-rich physics.
• Excellent knowledge of Python, PyTorch, and the distributed training of large-scale neural networks (FSDP, NCCL).
• Proven expertise in Diffusion Models, Flow Matching, and Transformers.
• Hands-on experience deploying learning-based controllers on real robot hardware.
• Experience with Reinforcement Learning and simulation environments (e.g., IsaacLab, MuJoCo)

Benefits

• Competitive compensation
• Enhanced pension plan
• Enhanced holiday & paid leave perks
• Relocation & permit sponsorship
• 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 wi