Sereact

<h2>Who We Are:</h2>We are a rapidly growing embodied AI company revolutionizing human labor. Leveraging cutting-edge robotics and advanced artificial intelligence, we develop transformative technologies that redefine how work is done across multiple industries—empowering businesses to streamline operations, boost productivity, and unlock new possibilities.<h2>Overview:</h2>We are looking for a world-class robotics professionals to join our R&amp;D hub in the Zurich area. In this role, you will be at the forefront of developing Vision-Language-Action (VLA) models that enable robots to understand and interact with the world with unprecedented generalization. You will work on the intersection of large-scale foundation models and real-world robotic execution, bridging the gap between state-of-the-art research and deployed embodied intelligence.<h2>Your Responsibilities:</h2>Research &amp; Development:<ul><li>Design, implement, and scale VLA models and foundation architectures for robotic manipulation and navigation.</li></ul>Scaling Laws &amp; Data:<ul><li>Develop strategies for multi-modal data collection, synthetic data generation, and efficient fine-tuning of large-scale models.</li></ul>Algorithm Optimization:<ul><li>Optimize model inference for real-time robotic applications without compromising reasoning capabilities.</li></ul>Publication &amp; Visibility:<ul><li>Contribute to the global research community by publishing high-impact papers at top-tier conferences (NeurIPS, CVPR, ICRA, CoRL, etc.).</li></ul>Collaboration:<ul><li>Work closely with the Core Robotics and Hardware teams to integrate AI models into our physical platforms.</li></ul><h2>Qualifications:</h2>Academic Excellence: <ul><li>PhD or Master’s degree in Computer Science, Machine Learning, Robotics, or a related field, with a focus on Deep Learning and Computer Vision.</li></ul>Proven Research Track Record: <ul><li>Significant publications and citations at major conferences such as NeurIPS, CVPR, ICCV, ICRA, IROS, or CoRL.</li></ul>Professional Background: <ul><li>Experience working in leading AI research environments</li></ul>Technical Mastery: <ul><li>Deep expertise in PyTorch or JAX, experience with Transformers, Diffusion Models, and Large Language Models (LLMs).</li></ul>Domain Knowledge: <ul><li>Strong understanding of Vision-Language models and their application to Action/Control loops in robotics.</li></ul><h2>Location:</h2>Zurich Area, Switzerland: <ul><li>This role is based in our Zurich office, offering a vibrant ecosystem for robotics and AI.</li></ul><h2>What We Offer:</h2><ul><li>Free meals at the workplace.</li><li>Flexible working hours and the option to work from home when needed.</li><li>Direct collaboration with founders and world-leading AI experts.</li><li>Access to large-scale compute clusters and proprietary robotic datasets.</li><li>A key role in shaping the future of embodied AI.</li><li>Competitive compensation and a relocation package for the Zurich area</li></ul>

Member of Technical Staff (m/f/d)

<h2>Research Engineer, Manipulation Data &amp; Teleoperation — Zurich</h2>This role owns the data generation layer of Sereact's VLA stack: teleoperation systems and data collection infrastructure that feed Cortex, built from our Zurich research hub.<h2>About Sereact</h2>Sereact is a Series B embodied-AI company. Cortex, our VLA model, is deployed in live warehouse robotic cells across the EU and US. Zurich is our newest research hub, focused on the manipulation and control problems that sit underneath Cortex.<h2>The role</h2>This is a Research Engineer position. It is scoped to the data generation layer of the VLA stack: teleoperation hardware and software, retargeting pipelines that map human demonstrations onto robot hands, and the data collection infrastructure that feeds Cortex. It requires building the systems that produce the data those models train on, and working closely with the training team on what that data needs to look like.<h2>What you'll do</h2><ul><li>Build and operate teleoperation systems for dexterous manipulation, including retargeting algorithms that map human hand and arm motion onto robot end-effectors</li><li>Design and maintain scalable, UMI-style data collection hardware and software that other engineers at Sereact rely on</li><li>Benchmark control and retargeting approaches using rigorous, human-factors-informed methodology</li><li>Instrument and support the physical robots deployed in the Zurich hub, including day-to-day work on the control stack</li><li>Work with the model-training team to define what data they need and close the loop on data quality</li><li>Build tooling or infrastructure outside your immediate brief when it unblocks the wider team</li></ul><h2>What you'll bring</h2><ul><li>MSc (or equivalent, in progress) in robotics, mechanical engineering, or a closely related field, with a thesis or capstone project on manipulation, teleoperation, or retargeting</li><li>Hands-on experience building a data collection device or system for robot learning (UMI or a comparable system), not just operating one someone else built</li><li>Working knowledge of retargeting algorithms for mapping human input onto robot hands or end-effectors</li><li>1 to 2 years of combined research, internship, or industry experience in robotics, mechatronics, or a related engineering discipline</li><li>Software and systems engineering skills strong enough to build and maintain infrastructure other engineers rely on, not only research-grade prototypes</li><li>Comfortable working as an individual contributor in a small, still-forming team</li></ul><h2>Nice to have</h2><ul><li>A conference submission on manipulation, teleoperation, or retargeting where the candidate is an author (an MSc thesis submitted to a venue like CoRL counts; supervising a student team whose own work was later published does not)</li><li>Teaching or TA experience in a robotics course</li><li>Some exposure to large-model training, even without an independent training record</li><li>A concrete example of building something outside the formal role brief because the team needed it</li></ul><h2>Location:</h2>Zurich Area, Switzerland: <ul><li>This role is based in our Zurich office, offering a vibrant ecosystem for robotics and AI.</li></ul><h2>What We Offer:</h2><ul><li>Free meals at the workplace.</li><li>Flexible working hours and the option to work from home when needed.</li><li>Direct collaboration with founders and world-leading AI experts.</li><li>Access to large-scale compute clusters and proprietary robotic datasets.</li><li>A key role in shaping the future of embodied AI.</li><li>Competitive compensation and a relocation package for the Zurich area</li></ul>

Research Engineer (m/f/d)

<h2>Who We Are:</h2>We build the intelligence that lets robots sense, reason, and act in the real world—moving beyond the lab and into everyday industrial settings like warehouses and factories. Our technology closes the automation gaps that traditional systems can’t solve. We are on a mission to redefine how physical work gets done, and we’re looking for curious, bold thinkers to help shape the future of robotics with us.<h2>Overview:</h2>We are seeking a highly motivated Research Intern to contribute to our work on task decomposition and multimodal fusion for imitation learning in robotic manipulation. This internship is ideal for students or early-stage researchers passionate about applying machine learning, computer vision, and robotics to real-world industrial automation challenges.<h2>Your Responsibilities:</h2><ul><li>Develop and evaluate task decomposition methods for complex robotic manipulation tasks.</li><li>Investigate multimodal sensor fusion (e.g., vision, force, tactile) techniques to improve policy learning.</li><li>Implement and benchmark imitation learning pipelines using both simulated and real-world robotic setups.</li><li>Collaborate with our engineering team to transfer research outcomes to prototype systems.</li><li>Document and present findings to both technical and non-technical stakeholders.</li></ul><h2>Qualifications:</h2><h3>Must Have:</h3><ul><li>Enrolled in a Master’s or PhD program in Robotics, Machine Learning, Computer Vision, or a related field with a minimum GPA of 1.7 (German scale).</li><li>OR GitHub repository with at least 5 stars</li></ul><h3>Other Requirements:</h3><ul><li>Familiarity with reinforcement learning, imitation learning, or behavior cloning methods.</li><li>Hands-on experience with robotic platforms or simulation environments (e.g., PyBullet, Isaac Gym).</li><li>Strong programming skills in Python; familiarity with PyTorch or TensorFlow is a plus.</li><li>Excellent problem-solving skills and the ability to work independently.</li></ul><h2>What We Offer:</h2><ul><li>Flexible working hours</li><li>Option to work from home when needed</li><li>A motivated team and an open corporate culture</li></ul>

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