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Member of Technical Staff - Embodied AI Researcher (Zurich)

sereact · Zurich

Nouveau
Senior 🇬🇧 English
PyTorch JAX Transformers Diffusion Models Large Language Models Computer Vision Deep Learning

Description du poste

About the role

A rapidly growing embodied AI company is looking for a world-class robotics professional to join its R&D hub in the Zurich area. You will help develop Vision-Language-Action (VLA) models that let robots understand and interact with the world, working at the intersection of large-scale foundation models and real-world robotic execution.

Key responsibilities

  • 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
  • Publish high-impact papers at top-tier conferences such as NeurIPS, CVPR, ICRA and CoRL
  • Work closely with the Core Robotics and Hardware teams to integrate AI models into physical platforms

Required profile

  • 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
  • Strong understanding of Vision-Language models applied to action/control loops in robotics

Required skills

  • Deep expertise in PyTorch or JAX
  • Experience with Transformers, Diffusion Models and Large Language Models

What we offer

  • Free meals at the workplace
  • Flexible working hours and the option to work from home when needed
  • Direct collaboration with founders and world-leading AI experts
  • Access to large-scale compute clusters and proprietary robotic datasets
  • Competitive compensation and a relocation package for the Zurich area

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Source : ats:ashby

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