Job Description
DESCRIPTION
Are you excited about developing algorithms and models to power Amazon's next generation robotic storage systems? 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. We are looking for enthusiastic scientists for a variety of roles.
The Research team at Amazon Robotics is seeking a passionate, collaborative, hands-on Applied Scientist to develop planning and scheduling algorithms to support Amazon's next generation robotic storage systems. The focus of this position workflow optimization and robot task-assignment. It includes designing and evaluating planning and scheduling algorithms using a combination of machine learning, reinforcement learning, and optimization methods as appropriate. This work spans from research such optimal decision making, to policy learning, to experimenting using simulation and modeling tools, to running large-scale A/B tests on robots in our facilities.
The ideal candidate for this position will be familiar with planning or learning algorithms at both the theoretical and implementation levels. You will have the chance to solve complex scientific problems and see your solutions come to life in Amazon’s warehouses!
Key job responsibilities
- Research design - How should solve a particular research problem
- 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
On a typical day in this role you will work to progress your research projects, meet with engineering, systems, and solutions stakeholders, brainstorm with other scientists on the team, and participate in team processes. You will follow your research projects though the entire life cycle of design, implementation, evaluation, analysis, and will communicate your findings and results through technical papers and reports. You will work with engineering teams to incorporate your models and analyses into system and process designs.
Amazon offers a full range of benefits that support 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
Our multi-disciplinary science team includes scientists with backgrounds in simulation, planning and scheduling, grasping and manipulation, machine learning, reinforcement learning, and operations research. 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
* Learning how to adapt system behavior to varying operating conditions
* Co-design of robotic logistics processes and the algorithms to optimize them
Our team also serves as a hub to foster innovation and support scientists across Amazon Robotics. We also coordinate research engagements with academia, such as the Robotics section of the Amazon Research Awards.
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 any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience applying theoretical models in an applied environment
- Experience building machine learning models or developing algorithms for business application
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
Job Tags
Full time, Temporary work, Seasonal work,