Applied Scientist - Motion Planning & Control, Amazon Robotics
Applied Scientist - Motion Planning & Control, Amazon Robotics
Amazon
Internet, Onlinemedien
- Berlin
- Vollzeit
Vor Ort
Applied Scientist - Motion Planning & Control, Amazon Robotics
Über diesen Job
Stellen-ID: 2905746 | Amazon Development Center Germany GmbH
BESCHREIBUNG
Do you want to create intelligent, adaptable robots with global impact? At Amazon Robotics, our collaborative team builds high-performance, real-time robotic systems that perceive, plan, and act intelligently alongside humans—at Amazon scale. Our mission is to enable robots to interact safely, efficiently, and fluently through the complex challenges of a company that sells everything, everywhere. We target high-impact algorithmic unlocks in areas such as scene and activity understanding, large-scale generative models, closed-loop control, robotic grasping and manipulation—all of which have high-value impact for our current and future fulfillment networks. Our solutions enable robots to learn from their own experiences, from each other, and from humans to build intelligence that feeds itself.
We are seeking an Applied Scientist to join our Motion Planning and Control team creating a fleet of manipulation robots at scale. You will apply the latest trends in research to solve real-world problems alongside a world-class team of experts in motion planning, computer vision, deep learning, intelligent control, and semi-supervised and unsupervised learning. We target high-impact algorithmic unlocks in areas such as scene and activity understanding, closed-loop control, robotic grasping, and manipulation in high-contact environments. Your contributions will drive the development and scaling of advanced robotic systems capable of handling complex, dynamic environments and transforming how robots interact with the world around them.
Key job responsibilities
• Research, design, implement and evaluate complex motion planning and control algorithms that improve the performance of systems deployed in real-world conditions.
• Create experiments and prototype implementations of new learning algorithms and prediction techniques.
• Work closely with software engineering team members to drive scalable, real-time implementations.
• Collaborate with perception, machine learning and robotic controls experts to implement and deploy algorithms, such as machine learning models.
• Collaborate closely with hardware engineering team members on developing systems from prototyping to production level.
• Represent Amazon in academia community through publications and scientific presentations.
• Work with stakeholders across hardware, science, and operations teams to iterate on systems design and implementation.
GRUNDQUALIFIKATIONEN
- PhD in engineering, computer science, machine learning, robotics, or related field
- Expertise in motion planning and/or control for robotic manipulators
- Experience in publishing at major robotics and related conferences (e.g. ICRA, IROS, RSS, CORL) or journals (e.g. IJRR, TRO).
- Experience programming in Java, C++, Python or related language
BEVORZUGTE QUALIFIKATIONEN
- Expertise in algorithmic and ML-based motion generation approaches (e.g. reinforcement learning).
- Expertise in closed-loop control with computer vision (e.g. high-frequency visual feedback) and/or haptic sensory feedback
- Experience with interdisciplinary developments that involve hardware, software, and algorithm co-design.
- Demonstrated experience incubating and productionizing new technology from idea generation through large-scale deployment.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
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