SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Sereact is a Series B embodied AI company developing robotics and artificial intelligence technologies to transform human labor across industries. We are seeking a world-class robotics professional to join our R&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 at 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.
Key responsibilities include:
- Design, implement, and scale VLA models and foundation architectures for robotic manipulation and navigation
- Develop strategies for multi-modal data collection, synthetic data generation, and efficient fine-tuning of large-scale models
- Optimize model inference for real-time robotic applications without compromising reasoning capabilities
- Contribute to the global research community by publishing high-impact papers at top-tier conferences (NeurIPS, CVPR, ICRA, CoRL, etc.)
- Work closely with the Core Robotics and Hardware teams to integrate AI models into physical platforms
You will have direct collaboration with founders and world-leading AI experts, access to large-scale compute clusters and proprietary robotic datasets, and flexible working hours with the option to work from home when needed.
REQUIREMENTS:
- PhD or Master's degree in Computer Science, Machine Learning, Robotics, or a related field, with a focus on Deep Learning and Computer Vision
- Significant publications and citations at major conferences such as NeurIPS, CVPR, ICCV, ICRA, IROS, or CoRL
- Experience working in leading AI research environments
- Deep expertise in PyTorch or JAX, experience with Transformers, Diffusion Models, and Large Language Models (LLMs)
- Strong understanding of Vision-Language models and their application to Action/Control loops in robotics