Applied Scientist, Workplace Health & Safety

Amazon•Nashville, TN

About The Position

Are you driven by the challenge of solving complex problems that directly impact the safety and well-being of millions of Amazon Associates worldwide? Do you want to push the boundaries of AI to build innovative solutions that make workplaces safer and more efficient? If so, we invite you to join our WHS DataTech team as an Applied Scientist and take your career to the next level! At WHS DataTech, we leverage Large Language Models (LLMs), Computer Vision, and AI-driven innovations to develop industry-leading solutions that proactively enhance workplace safety. Our work spans real-time risk assessment, predictive analytics, and AI-powered insights, all aimed at creating a safer work environment at scale. As an Applied Scientist specializing in LLMs and Computer Vision, you will play a pivotal role in shaping our next-generation safety solutions. You’ll be at the forefront of innovation, designing and implementing AI-powered features that redefine workplace safety. Your work will drive strategic decisions, optimize system architecture, and influence best practices, ensuring our technology remains industry-leading.

Requirements

3+ years of building models for business application experience
Experience in patents or publications at top-tier peer-reviewed conferences or journals
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
PhD degree in Computer Science or Computer engineering
A formal PhD degree in Computer Science or Computer engineering or can be replaced by 5 years of relevant experience on top of a MSc, and 7 years on top of a BSc.

Nice To Haves

Experience using Unix/Linux
Experience in professional software development

Responsibilities

Apply LLM model to analyze complex unstructured datasets and extract meaningful insights.
Collaborate with software engineers to implement and deploy machine learning (LLM or CV) solutions.
Conduct experiments and evaluate model performance, iterating and improving as needed.
Stay up-to-date with the latest advancements in machine learning and related fields.
Collaborate with cross-functional teams to understand business needs and identify areas for application of machine learning.
Present findings and recommendations to stakeholders and contribute to the overall research and development strategy.