Research Scientist II, Grocery ECO

Amazon.com Inc.; Bengaluru; Presencial; INR 4.000.000 - 7.000.000; Jornada completa

Descripción de la vacante

Amazon Inc. is seeking a Research Scientist to design, develop, and deploy machine learning and computer vision models at scale in the Amazon grocery domain.

You will own the model lifecycle from experimentation to deployment and work with engineering, product, and business teams to deliver production-ready solutions that improve customer shopping experiences. The role emphasizes rigorous experimentation, reproducible results, and staying current with state-of-the-art CV and ML research.

Formación

• PhD or Master’s degree required or equivalent experience.
• 3+ years of building ML models for business applications.
• Experience in applying scientific principles to business problems.
• Experience with neural deep learning methods and machine learning.
• Experience programming in Java, C++, Python or related language.

Responsabilidades

• Design, train, and evaluate ML/vision models for grocery-domain problems.
• Conduct rigorous exploratory data analysis to characterize challenges and inform modeling decisions.
• Design and execute offline and online evaluation frameworks and diagnose failures.
• Build and improve data pipelines and annotation workflows for model training.
• Communicate results and recommendations clearly to engineering, product, and business stakeholders.

Conocimientos

Machine learning

Deep learning

Multimodal learning

Data analysis

Stakeholder communication

Educación

PhD, or Master’s degree

Herramientas

Java

C++

Python

Descripción del empleo

We are looking for a talented Research Scientist to join our team. In this role, you will design, develop, and deploy machine learning and computer vision models that solve real-world problems at scale in the Amazon grocery domain. You will work closely with engineering, product, and business teams to turn complex technical challenges into production-ready solutions, and own the model development lifecycle from experimentation through deployment. You will bring scientific rigor to every stage — from data analysis and model design to evaluation and iteration. This is a high-impact role where your models will directly improve the shopping experience for millions of customers in Amazon grocery stores.

Key job responsibilities

• Design, train, and evaluate computer vision and machine learning models for complex grocery-domain problems including product identification, shelf perception, and in-store scene understanding — iterating rapidly from prototype to production-quality solutions
• Conduct rigorous exploratory data analysis to characterize domain-specific challenges (image variability, catalog gaps, label noise) and translate findings into actionable modeling decisions
• Design and execute offline and online evaluation frameworks — defining metrics that capture both model performance and downstream business impact, and diagnosing failure modes to prioritize improvements
• Build and improve data pipelines and annotation workflows that feed model training, including active learning strategies to maximize label efficiency
• Communicate technical results, trade-offs, and recommendations clearly to engineering, product, and business stakeholders — connecting model behavior to customer experience outcomes
• Stay current with state-of-the-art research in computer vision, multimodal learning, and representation learning — evaluating and adapting promising techniques to team-specific problems
• Contribute to a culture of scientific rigor through reproducible experimentation, thorough documentation, peer code and design reviews, and raising the quality bar for the team

A day in the life

• As a Research Scientist on the GRAISE team, you'll spend your days analyzing model performance from overnight experiments, and prototyping new approaches using multimodal learning with store video and sensor data. You'll present findings to product and business stakeholders, translating technical results into actionable recommendations. Throughout the day, you'll balance rigorous scientific thinking with practical engineering constraints, knowing your work directly improves the shopping experience for millions of customers in Amazon grocery stores.

About the team

The GRAISE team (Grocery, Retail & In-Store Experience) within World Wide 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.

Basic Qualifications

• - PhD, or Master's degree
• - Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
• - Experience analyzing both experimental and observational data sets
• - 3+ years of building machine learning models for business application experience
• - Experience programming in Java, C++, Python or related language
• - Experience with neural deep learning methods and machine learning

Preferred Qualifications

• - Knowledge of R, MATLAB, Python or similar scripting language
• - 3+ years of applied research experience
• - Knowledge of deep learning, machine learning and statistics
• - Experience in patents or publications at top-tier peer-reviewed conferences or journals

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 visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.