Postdoctoral scientists at Amazon Robotics focus on solving research-intensive business problems by exploring new research ideas, accelerating scientific innovation and impact, and publishing their work in top-tier, peer-reviewed scientific venues.

Postdoctoral scientists raise the scientific bar across Amazon by diving deep into exploratory areas of research to enhance the customer experience.

This postdoctoral scientist will be exploring and building upon the state of the art in the domain of Foundation Models and Generative AI for dynamic, multi-robot systems.

The research will cover extensions / adaptations to the Transformer model architecture and data representations to accommodate the specific nature of our multi-robot data.

For example, in physical systems, hallucinations could result in physical objects that appear, disappear, or teleport in ways that are physically inconsistent or infeasible.

As a result, example research questions include (i) What data representations and model architectures are most suitable for our multi-robot systems?

ii) How can we create a model that enforces physical constraints? (ii) How can we derive application models that will focus on certain robotic tasks / problems?

The Research Science, Applied Science, and Data Science team (RAD) focuses on planning and optimization problems where robotic systems are faced with complex decisions.

The RAD Data Science (RAD-DS) team builds upon the advancements in Data Science, Machine Learning, and Artificial Intelligence (ML and AI) to enable more performant, scalable, adaptive, and robust AR systems.

We develop ML models to measure and improve performance. As a research and innovation team, we work with product and engineering teams to research, develop, and transfer new machine learning models, algorithms, and solutions that improve the performance of AR components, systems, and systems of systems.

We work across verticals to build and integrate new AI-driven methods that push the limit of performance.

Key job responsibilities

• Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community.
• Publish your innovation in top-tier academic venues and hone your presentation skills.
• Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.

We are open to hiring candidates to work out of one of the following locations :

Westborough, MA, USA

BASIC QUALIFICATIONS

• PhD in a relevant field, received within 2 years of starting the program
• Proven publication record in Machine Learning, Robotics, Computer Vision, AI, Computer Science, Econ, or other related technical fields
• Experience in data science and quantitative research
• Proficiency in technologies relevant to the subfield

PREFERRED QUALIFICATIONS

• Ability to independently deliver results in a fast-paced environment
• Publications at top-tier, peer-reviewed conferences and / or journals
• Exceptional verbal and written communication skills
• Expert knowledge in modeling and performance, operationalization, and scalability of scientific techniques and establishing decision strategies
• Research experience in Machine Learning, Deep Learning, and / or Transformer architectures / Large Language Models (LLMs)

Required application materials :

• CV, which lists all peer-reviewed publications and conferences,
• Research statement that outlines your research achievements and future research interests, and
• A journal article or book chapter that demonstrates your domain expertise.

Last updated : 2024-04-28