The Item and Relationship Identity Systems (IRIS) team in WW Amazon Stores is looking for a passionate and talented Principal Applied Scientist with a strong background in deep learning and multimodal AI, to lead the development of industry-leading multimodal machine learning models to help us make the world’s best product catalog even better.
In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, large multimodal models, and services to infer product-to-product relationships that matter to our customers.
You will work in a collaborative environment where you can experiment with massive data from the world’s largest product catalog, work on challenging problems, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers.
An information-rich and accurate product catalog is a strategic asset for Amazon. We use cutting edge machine learning techniques to proactively identify relationships between products within the Amazon product catalog.
This problem is challenging due to sheer scale (billions of products in the catalog), diversity (products ranging from electronics to groceries to instant video across multiple languages), multitude of input sources (millions of sellers contributing product data with different quality) and varied relationship types.
Key job responsibilities
As a Principal Applied Scientist with the IRIS team, you will lead the development of novel algorithms and modeling techniques to advance the state of the art with multimodal systems.
Your work will directly help our customers and will power unrivaled product discovery, inform customer buying decisions, offer a large selection, and position Amazon as the first stop for shopping online.
You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence.
You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice.
You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development.
You will be technically fearless and with a passion for building scalable science and engineering solutions.
A day in the life
We love solving challenging and hard problems in our quest to innovate on behalf of our customers. We push the boundaries to leverage and invent technologies which help create unrivaled experiences for our customers to help us move fast in a growing and changing environment.
We use data to guide our decisions, work closely with our engineering and product counterparts, and partner with other Science teams to learn and guide in an environment of innovation.
About the team
The IRIS team has a mission to push the envelope with multimodal LLMs and Gen AI to provide the best-possible eCommerce experience for our customers.
We push the boundaries of advanced ML and generative AI techniques to scale the inputs for hundreds of billions of dollars of annual revenue for our e-commerce business.
We are open to hiring candidates to work out of one of the following locations :
Seattle, WA, USA
BASIC QUALIFICATIONS
- PhD with specialization in artificial intelligence, natural language processing, or machine learning
- 10+ years of combined academic and research experience.
- Functional thought leader, sought after for key tech decisions and influence ideas to executive level decision maker.
- Mentors and trains the research scientist community on complex technical issues.
- Experience developing software in traditional programming languages (C++, Java, etc..).
- Excellent written and spoken communication skills
PREFERRED QUALIFICATIONS
- Experience with deep learning frameworks
- Experience with LLMs and multimodal architectures
- Experience with generative deep learning models
- Strong publication record in top-tier journals and conferences.
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