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.

Reinforcement learning is transforming our robotic intelligence, enabling autonomous behavior without human guidance. We are seeking a Senior AI Engineer with deep expertise in reinforcement learning and deep learning, including supervised and self-supervised learning, to lead our engineering team. Your role will involve leveraging both simulated and real-world data to address practical challenges. If you are passionate about advancing AI and developing innovative solutions, join us in shaping the future of intelligent robotics.

What you’ll be doing

Develop cutting-edge reinforcement learning algorithms to enable robots to autonomously execute motor commands based on raw sensor input.
Design, test, and refine your algorithms to meet the demands of complex real-world locomotion, autonomy and manipulation tasks.
Collaborate with the computer vision and imitation learning team to innovate methods that leverage both simulated and real-world data.
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.

What you’ll be doing

Develop cutting-edge reinforcement learning algorithms to enable robots to autonomously execute motor commands based on raw sensor input.
Design, test, and refine your algorithms to meet the demands of complex real-world locomotion, autonomy and manipulation tasks.
Collaborate with the computer vision and imitation learning team to innovate methods that leverage both simulated and real-world data.
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.

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.
Strong deep learning fundamentals, including supervised and self-supervised learning techniques, and reinforcement learning, including Markov Decision Processes (MDPs), neural network architectures, policy optimization algorithms, model-based vs. model-free RL, exploration-exploitation strategies, value function methods, transfer learning, domain adaptation, sim-to-real transfer, etc.
Strong background in robotics including autonomy and/or manipulation.
Experience with deploying artificial neural networks on hardware platforms.
Ability to write production-level code in modern C++.
Ability to prototype algorithms and train deep neural networks in Python.

What you’ll be doing

Develop cutting-edge reinforcement learning algorithms to enable robots to autonomously execute motor commands based on raw sensor input.
Design, test, and refine your algorithms to meet the demands of complex real-world locomotion, autonomy and manipulation tasks.
Collaborate with the computer vision and imitation learning team to innovate methods that leverage both simulated and real-world data.
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.

What you’ll be doing

Develop cutting-edge reinforcement learning algorithms to enable robots to autonomously execute motor commands based on raw sensor input.
Design, test, and refine your algorithms to meet the demands of complex real-world locomotion, autonomy and manipulation tasks.
Collaborate with the computer vision and imitation learning team to innovate methods that leverage both simulated and real-world data.
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.

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.
Strong deep learning fundamentals, including supervised and self-supervised learning techniques, and reinforcement learning, including Markov Decision Processes (MDPs), neural network architectures, policy optimization algorithms, model-based vs. model-free RL, exploration-exploitation strategies, value function methods, transfer learning, domain adaptation, sim-to-real transfer, etc.
Strong background in robotics including autonomy and/or manipulation.
Experience with deploying artificial neural networks 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.

What you’ll be doing

Develop cutting-edge reinforcement learning algorithms to enable robots to autonomously execute motor commands based on raw sensor input.
Design, test, and refine your algorithms to meet the demands of complex real-world locomotion, autonomy and manipulation tasks.
Collaborate with the computer vision and imitation learning team to innovate methods that leverage both simulated and real-world data.
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.

What you’ll be doing

Develop cutting-edge reinforcement learning algorithms to enable robots to autonomously execute motor commands based on raw sensor input.
Design, test, and refine your algorithms to meet the demands of complex real-world locomotion, autonomy and manipulation tasks.
Collaborate with the computer vision and imitation learning team to innovate methods that leverage both simulated and real-world data.
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.

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.
Strong deep learning fundamentals, including supervised and self-supervised learning techniques, and reinforcement learning, including Markov Decision Processes (MDPs), neural network architectures, policy optimization algorithms, model-based vs. model-free RL, exploration-exploitation strategies, value function methods, transfer learning, domain adaptation, sim-to-real transfer, etc.
Strong background in robotics including autonomy and/or manipulation.
Experience with deploying artificial neural networks on hardware platforms.
Ability to write production-level code in modern C++.
Ability to prototype algorithms and train deep neural networks in Python.

What you’ll be doing

Develop cutting-edge reinforcement learning algorithms to enable robots to autonomously execute motor commands based on raw sensor input.
Design, test, and refine your algorithms to meet the demands of complex real-world locomotion, autonomy and manipulation tasks.
Collaborate with the computer vision and imitation learning team to innovate methods that leverage both simulated and real-world data.
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.

What you’ll be doing

Develop cutting-edge reinforcement learning algorithms to enable robots to autonomously execute motor commands based on raw sensor input.
Design, test, and refine your algorithms to meet the demands of complex real-world locomotion, autonomy and manipulation tasks.
Collaborate with the computer vision and imitation learning team to innovate methods that leverage both simulated and real-world data.
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.

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.
Strong deep learning fundamentals, including supervised and self-supervised learning techniques, and reinforcement learning, including Markov Decision Processes (MDPs), neural network architectures, policy optimization algorithms, model-based vs. model-free RL, exploration-exploitation strategies, value function methods, transfer learning, domain adaptation, sim-to-real transfer, etc.
Strong background in robotics including autonomy and/or manipulation.
Experience with deploying artificial neural networks 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.

Senior Ai Engineer - Reinforcement Learning

Job Description

What you’ll be doing

What you’ll be doing

What you must have

What you’ll be doing

What you’ll be doing

What you must have

Get some bonus points

What you’ll be doing

What you’ll be doing

What you must have

What you’ll be doing

What you’ll be doing

What you must have

Get some bonus points