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Senior AI Engineer - VLA Foundation Model

CompraTica Empleos

EMP:Technology
Zürich
Tiempo Completo
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Descripción

RIVR, part of Amazon is a robotics company pioneering Physical AI through real-world doorstep delivery.

Founded in 2024 as an ETH Zurich spin-off, RIVR developed wheeled-legged robots designed to operate in complex, unstructured environments such as stairs, gates, doors, and uneven urban terrain.

We believe that achieving general physical intelligence requires solving real customer problems in the real world, where robots can learn from rich operational data at scale.

  • Following our acquisition by Amazon in March 2026, we are continuing this mission with greater reach and speed.

By combining custom robot hardware, onboard autonomy, and cloud-based coordination, RIVR, part of Amazon is building the next generation of safe, reliable autonomous robots for last-mile delivery.

Descripción del Puesto

  Our fleet of delivery robots operates globally today, generating vast amounts of robotic real-world data

By utilizing state-of-the-art Vision-Language-Action (VLA) models, large-scale generalist models (like Transformers), generative AI, and similar methods, we can leverage this pool of data to significantly enhance its autonomy, navigation, and manipulation.

Habilidades

In this role, you will develop multi-modal models that enable robots to autonomously generate actions from demonstrations, real-time sensor data, and natural language commands.

We are seeking an expert in VLA models, imitation learning, and generative AI techniques with a deep knowledge of supervised, and self-supervised learning algorithms.

If you are passionate.

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pushing the boundaries of AI we invite you to join us in shaping the future of intelligent robotics.    What you’ll be doing Develop and implement cutting-edge Vision-Language-Action (VLA) models, generalist robot transformers, and imitation learning algorithms (e.g., diffusion policies) to enable robots to autonomously execute complex tasks

Design, test, and refine your algorithms to meet the demands of complex real-world autonomy and navigation task.

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