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15 May
26 May
The Amazon Robotics team is seeking an experienced Applied Scientist to join our team. In this role you will apply the latest trends in research to solve real-world problems in robotics and AI. You will collaborate with a team of scientists and engineers building these applications. We holistically design, build, and deliver end-to-end robotic systems. Our team is also responsible for core infrastructure and tools that serve as the backbone of our robotic applications, enabling roboticists, machine learning scientists, software engineers, and hardware engineers to collaborate and deploy systems in the field.
Key job responsibilities
• Research, design, implement and evaluate complex computer vision and decision making algorithms integrating across multiple disciplines and leveraging machine learning.
• 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 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.
- Experience in publishing at major robotics and related conferences (e.g. RSS, NIPS, ICRA, CVPR, CORL, ICCV) or journals (IJRR, IEEE TRO, JMLR).
- Experience programming in Java, C++, Python or related language
- Experience in delivering customer-facing results with computer vision models and ML model training pipelines
- Experience in one or more relevant technical areas: robotics, computer vision, machine learning, sensors, real-time systems, embedded systems, distributed systems, or simulation.
- Experience with interdisciplinary developments that involve hardware, software, and algorithm co-design.
- Expertise building and testing real-time systems.
- Demonstrated experience incubating and productionizing new technology from idea generation through implementation.
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.
m/w/d
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Key job responsibilities
• Research, design, implement and evaluate complex computer vision and decision making algorithms integrating across multiple disciplines and leveraging machine learning.
• 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 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.
Basic qualifications
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field- Experience in publishing at major robotics and related conferences (e.g. RSS, NIPS, ICRA, CVPR, CORL, ICCV) or journals (IJRR, IEEE TRO, JMLR).
- Experience programming in Java, C++, Python or related language
- Experience in delivering customer-facing results with computer vision models and ML model training pipelines
Preferred qualifications
- PhD and relevant industry or academic research experience in developing algorithms for robotic computer vision and/or motion planning/control.- Experience in one or more relevant technical areas: robotics, computer vision, machine learning, sensors, real-time systems, embedded systems, distributed systems, or simulation.
- Experience with interdisciplinary developments that involve hardware, software, and algorithm co-design.
- Expertise building and testing real-time systems.
- Demonstrated experience incubating and productionizing new technology from idea generation through implementation.
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.
m/w/d
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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