Applied Scientist II, Decision Science and Technology (DST)

DESCRIPTION

We are looking for talented Applied Scientists who are adept at a variety of skills, especially with LLMs, use of edge devices, computer vision, or related foundational models that will accelerate our plans to generate high-quality defect detection mechanisms.

Our mission is to improve the reliability of equipment (conveyors, motors, belts), and effectively identify from sensors, images, and video specific actions on material handling equipment (MHE) that can prevent unplanned downtime. With millions of products available on Amazon.com comes variation in weight, size, material, and shape. We build products and systems to detect and prevent equipment downtime using a diverse set of classification and anomaly detection algorithms including LLMs. 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 AI predictive maintenance models, deploy scalable causal inference solutions to measure the impact of events, and optimize the reliability of conveyance helping Amazon scale for years to come.

As an Applied Scientist II, you will design, develop, and maintain scalable Artificial Intelligence 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.

Key job responsibilities

1. Design and implement scalable infrastructure that enables stacked deep learning models to detect a variety of defects in fractions of a second;
2. Design and implement anomaly detection and large language models to identify defects associated with customer packages;
3. Experiment and scale models to thousands of sites worldwide;
4. Collaborate with RME internal and external stakeholders and have a cross-team impact;
5. Create and share with audiences of varying levels technical papers and presentations.

About the team

We are a growing team of applied, research, and data scientists working together with an engineering team and product managers to create the next-generation IIoT platform for the Reliability and Maintenance Engineering org.

BASIC QUALIFICATIONS

1. PhD, or a Master's degree and experience in CS, CE, ML or related field;
2. Experience in patents or publications at top-tier peer-reviewed conferences or journals;
3. Experience programming in Java, C++, Python or related language;
4. Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing;
5. Experience in building machine learning models for business applications.

PREFERRED QUALIFICATIONS

1. Experience using Unix/Linux;
2. Experience in professional software development.

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 (here) to know more about how we collect, use, and transfer the personal data of our candidates.

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.

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 visitherefor more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

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