Sr. Applied Scientist, Decision Science and Technology (DST)
DESCRIPTION
Our mission is to improve the reliability of equipment (conveyance, motors, robotics), and optimize the maintenance and inventory management policies to support sites across our entire distribution network. We build products and systems to detect and prevent equipment downtime using a diverse set of algorithms, survival analysis, and large vision models. We screen over 150 million events every day, and process this data to create real time alerting systems. We are still day 1 and have an exciting roadmap to build computer vision models to automate defect detection and action material handling equipment, deploy scalable causal inference solutions to measure the impact of events, and optimize the reliability of miles of conveyance per site to help scale Amazon for years to come.
As a Sr. Applied Scientist, you will design, develop, and maintain scalable, Deep Learning models with automated training, validation, monitoring and reporting. You will work closely with other scientists and engineers to architect and develop new learning algorithms and prediction techniques. You will collaborate with product managers and engineering teams to design and implement scientific solutions for Amazon problems. Provide technical and scientific guidance to your team members. Contribute to the research community, by working with other scientists across Amazon and publish papers at peer reviewed journals and conferences.
We can hire scientist in a) Bellevue, b) Austin, c) Nashville, d) Denver, e) DC, and f) NYC
Key job responsibilities
• Drive software engineering best practice while designing the world's foremost distributed and scalable systems.
• Develop and deploy edge-to-cloud software framework for computer vision processing
• Design and develop innovative REST APIs and SDKs to deliver computer vision and machine learning capabilities
• Be responsible for the architecture of software solutions, determining current limitations and compatibility between subsystems, the selection of new concepts and methodology, and the development of major routines and utilities.
• Instill best practices for software development and documentation, making sure designs meet requirements, and delivering high quality software on tight schedules.
A day in the life
Sr. Applied Scientists within DST own the design, architecture, maintenance of Machine Learning models supporting initiatives related to computer vision applications at a network level. You will interact with other scientists on the team but to scale solutions you will travel to sites, interact with Field RME, Ops leadership, as well as other technical teams such as Amazon Fulfillment Technologies.
About the team
The Central Reliability and Maintenance Engineering, Decision Science and Technology (DST) team owns the design, deployment, and maintenance of an Artificial Intelligence/Computer Vision solution capable of automatically detecting defects in packages and taking action to ensure packages make it to customers in time. We are seeking a highly motivated and experienced Sr. Applied Scientist to join our team.
BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.