Research Scientist, Optimization, Planning and Task-Assignment, Amazon Robotics
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 Research 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 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
- Prototype implementation - Building key parts of algorithms or model prototypes
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 consult with engineering teams as they 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, 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 quantitative field research experience
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
- Experience analyzing both experimental and observational data sets
- Knowledge of R, MATLAB, Python or similar scripting language
- Experience in planning and optimization
PREFERRED QUALIFICATIONS
- Experience with any programming language such as Python, Java, C++
- Experience with experimental design
- Experience in machine learning, statistics, and deep learning
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.