Applied Scientist, Grocery, Retail & In-Store Experience (GRAISE)

Amazon • Seattle, WA

3d

About The Position

The GRAISE team (Grocery, Retail & In-Store Experience) within Worldwide Grocery
Store Tech (WWGST) builds foundational AI and machine learning systems that
power Amazon's in-store grocery technologies. We develop domain-specific models
that solve uniquely complex challenges in grocery — from smart shopping carts
and inventory intelligence to personalization and store operations. Our mission
is to create technology which makes grocery shopping more convenient,
economical, personalized, and enjoyable for customers while empowering retailers
with operational efficiency.

We are looking for a talented and motivated Applied Scientist to join our team.
In this role, you will design, develop, and deploy machine learning and computer
vision models and algorithms that solve real-world problems at scale. You will
work closely with engineering, product, and business teams to translate
ambiguous problems into rigorous scientific solutions, and you will own the
end-to-end development of models from ideation through production. This is a
high-impact role where your work will directly shape the intelligence layer of
Amazon's grocery ecosystem.

Requirements

• PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience
• 2+ years of building machine learning models or developing algorithms for business application experience
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
• Experience with popular deep learning frameworks such as MxNet and Tensor Flow
• Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

Nice To Haves

• Experience in patents or publications at top-tier peer-reviewed conferences or journals
• Experience with programming languages such as Python, Java, C++

Responsibilities

• Design and implement machine learning models to solve complex grocery-domain problems.
• Conduct exploratory data analysis and develop deep understanding of domain-specific data challenges.
• Collaborate with software engineers to productionize models and ensure reliability at scale.
• Define and track key metrics to evaluate model performance and business impact.
• Communicate findings and recommendations clearly to technical and non-technical stakeholders.
• Stay current with the latest research and evaluate applicability to team problems.
• Contribute to a culture of scientific rigor, experimentation, and continuous improvement.

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level