Swiss-Mile Robotics AG is a deep-tech startup that connects AI with the physical world through autonomous wheeled-legged robots. These robots are designed to revolutionize monitoring, security, logistics applications, and beyond. Backed by leading global venture capitalists, we are on a mission to enhance our team with world-class talent. Join our innovative team, renowned for pioneering robotic design and neural network applications in robotics that improve environmental understanding and decision-making. With a robust research foundation and notable contributions from ETH Zurich, we are leaders in translating artificial intelligence and robotics into practical, real-world applications. Your role will be to lead our efforts focused on enhancing our robots' ability to perceive and interpret their environments. You will work closely with our experts in reinforcement and imitation learning to integrate complex sensory data into our systems. You will be critical in utilizing extensive real-world data from diverse sensors to develop and upscale sophisticated models. Your expertise should encompass deep-learning-based computer vision and the latest AI applications, including image segmentation, object detection, and real-time decision-making for autonomous navigation and manipulation in robotics or autonomous driving. If you are passionate about pioneering advancements in AI and keen to lead transformative projects in robot navigation and manipulation, we invite you to join us in forging the future of intelligent robotics.
What you’ll be doing
Design and develop multi-modal, multi-task deep learning architectures to enhance our perception stack capabilities. Focus on advancing object detection, tracking, segmentation and scene understanding to build a world model which will form the basis for solving complex autonomy and manipulation challenges in robotics.
Lead the design, optimization, and deployment of neural networks on physical robotics platforms, improving environmental understanding and autonomous decision-making.
Investigate how deep learning can be applied to safety-critical, large-scale applications in real-world settings.
Develop and implement robust data management solutions for efficiently storing and handling data from robot deployments.
Build and refine data extraction, labeling, training, and evaluation pipelines to optimize AI performance and efficiency.
Collaborate closely with the reinforcement learning and imitation learning teams to integrate comprehensive AI solutions into robotics systems.
Stay current with the latest advancements in vision models, incorporating innovative techniques to enhance the development process.
Utilize both simulated and real-world data to train neural networks for detailed semantic scene understanding, continually improving platform capabilities.
Implement deployment-ready code for the real robot, optimized for the robot’s computational constraints.
Build, lead and mentor an exceptional team of software engineers.
Provide expert guidance to product managers and executives for strategic decision-making.
Create and maintain documentation, guidelines, and best practices to streamline knowledge sharing.
Improve coding standards and processes through active participation in code reviews.
What you must have
Master’s degree or higher in a relevant field such as Engineering, Robotics, or Machine Learning.
A minimum of five years of industry or research experience, with PhD experience applicable.
Deep technical expertise in semantic scene understanding, neural network architectures, robot decision-making, supervised learning, self-supervised learning, etc.
Strong background in robotics or autonomous driving.
Strong understanding of state-of-the-art vision models, with the ability to quickly grasp and apply new techniques to real-world problems.
Experience with deploying computer vision algorithms on hardware platforms.
Ability to write production-level code in modern C++.
Ability to prototype algorithms and train deep neural networks in Python.
Get some bonus points
PhD degree in Robotics, Engineering, Computer Science, Machine Learning or a similar discipline, or an equivalent amount of research experience.
Publications at top-tier conferences.
Experience in managing a software team.
We are looking forward to receive your application.
