Applied Scientist II

Role: Applied Scientist II

Location: North Reading MA

Contract

Job description

• Client is seeking exceptional talent to help develop the next generation that will transform automation at scale. We are building revolutionary robotic systems that combine cutting-edge AI sophisticated control systems and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale working with world-class teams pushing the boundaries of whats possible in robotic dexterous manipulation locomotion and human-robot interaction.
• This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models.
• At we leverage advanced robotics machine learning and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide working in sophisticated coordination to fulfill our mission of customer excellence.
• The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team thats revolutionizing how robots learn adapt and interact with their environment.
• Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration.

Key job responsibilities:

• Design and implement whole body control methods for balance locomotion and dexterous manipulation - Utilize state-of-the-art in methods in learned and model-based control - Create robust and safe behaviors for different terrains and tasks - Implement real-time controllers with stability guarantees
• Collaborate effectively with multi-disciplinary teams to co-design hardware and algorithms for loco-manipulation - Mentor junior engineer and scientists

Basic qualifications

• PhD or Masters degree and 2 years of applied research experience - Experience with imitation learning and reinforcement learning for whole-body control - Experience with methods such as hierarchical quadratic programming and model
• predictive control - Experience with simulation environments such as IsaacLab Mujoco Drake etc. - Experience with developing and deploying code for real-time controllers - Experience in state estimation from multiple sensor modalities

Preferred qualifications

• Experience programming in Java C Python or related language - Experience working effectively across cross-functional teams and partnering well with people at all levels within an organization
• PhD in Robotics with a focus on whole-body control
• Experience with low-level joint torque/impedance control
• Experience with teleoperation systems
• Experience with robotics frameworks for fast prototyping (Matlab ROS etc.)