What are the responsibilities and job description for the Applied Scientist, Amazon Robotics (AR) position at Amazon?
DESCRIPTION
Are you excited about developing AI/ML solutions to revolutionize robotics and automation? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale.
The Research team at Amazon Robotics is seeking a passionate hands-on Applied Scientist to innovate in the field of planning for fleets of mobile robots. The focus of this position is optimizing movement in warehouses that feature thousands of robots in constant motion moving inventory around the building. Relevant research topics include planning and scheduling for multi robot systems, multi-agent path finding, and developing ML models to render fleet behavior adaptable to varying operating conditions. The work includes eliciting and addressing basic research questions from AR's rich application settings, running large-scale A/B tests on robots in our facilities, and collaborating with engineering teams to deploy solutions in our vast robot fleet.
Key job responsibilities
* Research vision - Where should we be focusing our efforts
* Research delivery - Proving/dis-proving strategies in offline data or in simulation
* Production studies - Insights from production data or ad-hoc experimentation
* Production implementation - Building key parts of deployed algorithms or models
A day in the life
Amazon offers a full range of benefits for you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
About the team
You would join our Movement Science team that includes scientists with backgrounds in planning and scheduling, machine learning, and robotics. We develop novel planning algorithms and machine learning methods and apply them to real-word robotic warehouses, including:
- Planning and coordinating the paths of thousands of robots
- Dynamic allocation and scheduling of tasks to thousands of robots
- ML models that adapt system behavior to varying operating conditions
- Co-design of layouts and the algorithms to optimize movement on them
Our team is part the Research, Applied, and Data Science organization within Amazon Robotics, a hub to foster innovation and support scientists across Amazon Robotics.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4 years of CS, CE, ML or related field experience
- Experience programming in Java, C , Python or related language
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience with any of the following (preferably in the context of multi-robot/multi-agent systems): automated planning, scheduling, heuristic search, deep learning, transformer-based models, foundation models, robotics
PREFERRED QUALIFICATIONS
- Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms
- Depth and breadth in state-of-the-art approaches for at least one of multi-robot systems, machine learning, or AI planning.
- Experience with large-scale machine learning systems, including training efficiency analysis and distilling models for deployment
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with cross-domain/multi-task model training including datasets from diverse sources, balancing many axes of measurement in evaluation, and deploying to multiple products.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
