AI Engineering
Research Engineer - Generative Humanoid Motion Generation
Type
Full-time
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 deployment of humanoids. We are founded by leading scientists in robot reinforcement learning (ex-Nvidia, ex-ETH Zürich) and backed by leading international VC firms. Within a few months, we’ve gone from our first line of code to deploying real humanoid capabilities with our partners.
The Role:
We are looking for an expert in whole-body motion generation to strengthen our Zurich team.
Inspired by recent successes in neural avatars and computer graphics, we aim to apply similar principles to generate whole-body motions for our humanoid robots.
The goal of this position is to develop and deploy state-of-the-art multimodal models for robot trajectory generation.
Requirements
Hands-on experience in the development and training of diffusion or flow matching models. Ideally, this includes either training robotic imitation policies or training models to generate whole-body motions for human avatars.
Particularly:
PhD or master's degree in diffusion models/flow matching or learning-based trajectory generation with relevant project experience.
Strong research profile with a high track record of publications at top computer vision, graphics and/or robotic conferences, such as ICCV/ECCV, CVPR, SIGGRAPH, CORL, RSS, etc.
Excellent knowledge of Python, PyTorch, and hands-on experience in the training and fine-tuning of diffusion models and/or flow matching policies.
Experience in the deployment of learning-based trajectory generation for robotic systems.
Experience with modern GPU-based simulations such as Omniverse or Genesis.
Good knowledge of state-of-the-art machine learning architectures.
We are looking for a person who enjoys working in a team in a very dynamic and fast-moving environment, and who is able and willing to take ownership of projects and decisions.
Benefits
Competitive compensation
A front-row seat at one of Europe’s most ambitious robotics companies
An energetic, collaborative team with a bias for action
AI Engineering
Research Engineer - Generative Humanoid Motion Generation
Type
Full-time
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 deployment of humanoids. We are founded by leading scientists in robot reinforcement learning (ex-Nvidia, ex-ETH Zürich) and backed by leading international VC firms. Within a few months, we’ve gone from our first line of code to deploying real humanoid capabilities with our partners.
The Role:
We are looking for an expert in whole-body motion generation to strengthen our Zurich team.
Inspired by recent successes in neural avatars and computer graphics, we aim to apply similar principles to generate whole-body motions for our humanoid robots.
The goal of this position is to develop and deploy state-of-the-art multimodal models for robot trajectory generation.
Requirements
Hands-on experience in the development and training of diffusion or flow matching models. Ideally, this includes either training robotic imitation policies or training models to generate whole-body motions for human avatars.
Particularly:
PhD or master's degree in diffusion models/flow matching or learning-based trajectory generation with relevant project experience.
Strong research profile with a high track record of publications at top computer vision, graphics and/or robotic conferences, such as ICCV/ECCV, CVPR, SIGGRAPH, CORL, RSS, etc.
Excellent knowledge of Python, PyTorch, and hands-on experience in the training and fine-tuning of diffusion models and/or flow matching policies.
Experience in the deployment of learning-based trajectory generation for robotic systems.
Experience with modern GPU-based simulations such as Omniverse or Genesis.
Good knowledge of state-of-the-art machine learning architectures.
We are looking for a person who enjoys working in a team in a very dynamic and fast-moving environment, and who is able and willing to take ownership of projects and decisions.
Benefits
Competitive compensation
A front-row seat at one of Europe’s most ambitious robotics companies
An energetic, collaborative team with a bias for action
AI Engineering
Research Engineer - Generative Humanoid Motion Generation
Type
Full-time
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 deployment of humanoids. We are founded by leading scientists in robot reinforcement learning (ex-Nvidia, ex-ETH Zürich) and backed by leading international VC firms. Within a few months, we’ve gone from our first line of code to deploying real humanoid capabilities with our partners.
The Role:
We are looking for an expert in whole-body motion generation to strengthen our Zurich team.
Inspired by recent successes in neural avatars and computer graphics, we aim to apply similar principles to generate whole-body motions for our humanoid robots.
The goal of this position is to develop and deploy state-of-the-art multimodal models for robot trajectory generation.
Requirements
Hands-on experience in the development and training of diffusion or flow matching models. Ideally, this includes either training robotic imitation policies or training models to generate whole-body motions for human avatars.
Particularly:
PhD or master's degree in diffusion models/flow matching or learning-based trajectory generation with relevant project experience.
Strong research profile with a high track record of publications at top computer vision, graphics and/or robotic conferences, such as ICCV/ECCV, CVPR, SIGGRAPH, CORL, RSS, etc.
Excellent knowledge of Python, PyTorch, and hands-on experience in the training and fine-tuning of diffusion models and/or flow matching policies.
Experience in the deployment of learning-based trajectory generation for robotic systems.
Experience with modern GPU-based simulations such as Omniverse or Genesis.
Good knowledge of state-of-the-art machine learning architectures.
We are looking for a person who enjoys working in a team in a very dynamic and fast-moving environment, and who is able and willing to take ownership of projects and decisions.
Benefits
Competitive compensation
A front-row seat at one of Europe’s most ambitious robotics companies
An energetic, collaborative team with a bias for action
AI Engineering
Research Engineer - Generative Humanoid Motion Generation
Type
Full-time
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 deployment of humanoids. We are founded by leading scientists in robot reinforcement learning (ex-Nvidia, ex-ETH Zürich) and backed by leading international VC firms. Within a few months, we’ve gone from our first line of code to deploying real humanoid capabilities with our partners.
The Role:
We are looking for an expert in whole-body motion generation to strengthen our Zurich team.
Inspired by recent successes in neural avatars and computer graphics, we aim to apply similar principles to generate whole-body motions for our humanoid robots.
The goal of this position is to develop and deploy state-of-the-art multimodal models for robot trajectory generation.
Requirements
Hands-on experience in the development and training of diffusion or flow matching models. Ideally, this includes either training robotic imitation policies or training models to generate whole-body motions for human avatars.
Particularly:
PhD or master's degree in diffusion models/flow matching or learning-based trajectory generation with relevant project experience.
Strong research profile with a high track record of publications at top computer vision, graphics and/or robotic conferences, such as ICCV/ECCV, CVPR, SIGGRAPH, CORL, RSS, etc.
Excellent knowledge of Python, PyTorch, and hands-on experience in the training and fine-tuning of diffusion models and/or flow matching policies.
Experience in the deployment of learning-based trajectory generation for robotic systems.
Experience with modern GPU-based simulations such as Omniverse or Genesis.
Good knowledge of state-of-the-art machine learning architectures.
We are looking for a person who enjoys working in a team in a very dynamic and fast-moving environment, and who is able and willing to take ownership of projects and decisions.
Benefits
Competitive compensation
A front-row seat at one of Europe’s most ambitious robotics companies
An energetic, collaborative team with a bias for action
Affolternstrasse 42
8050 Zurich, Switzerland
Shape the Future
Whether you're interested in our product, partnerships, or joining our team, we'd love to hear from you
© 2025 Flexion Robotics AG
Shape the Future
Whether you're interested in our product, partnerships, or joining our team, we'd love to hear from you
© 2025 Flexion Robotics AG
Shape the Future
Whether you're interested in our product, partnerships, or joining our team, we'd love to hear from you
© 2025 Flexion Robotics AG
Shape the Future
Whether you're interested in our product, partnerships, or joining our team, we'd love to hear from you
© 2025 Flexion Robotics AG