Applied Scientist I, Grocery, Retail & In-Store Experience (GRAISE)
ADCI - Karnataka•3w ago
IN, KA, BengaluruOnsiteFull-time
Top focus
Applied Scientist
- We are looking for a talented Applied Scientist to join our team. In this role, you will design, develop
- 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
- business teams to turn complex technical challenges into production-ready solutions
- 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
- evaluate computer vision and machine learning models for complex grocery-domain problems including product identification, shelf perception
- 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 Own the model development lifecycle from experimentation through deployment — collaborating with software and ML engineers to ensure models meet latency, throughput
- reliability requirements at production scale Design and execute offline and online evaluation frameworks — defining metrics that capture both model performance and downstream business impact
- 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
- recommendations clearly to engineering, product
- business stakeholders — connecting model behavior to customer experience outcomes Stay current with state-of-the-art research in computer vision, multimodal learning
- 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
- raising the quality bar for the team A day in the life As an Applied Scientist on the GRAISE team, you'll spend your days analyzing model performance from overnight experiments, collaborating with engineers to deploy computer vision models to production
- 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
- enjoyable for customers while empowering retailers with operational efficiency
- Experience programming in Java, C++, Python or related language - Experience building machine learning models or developing algorithms for business application
- Experience implementing algorithms using both toolkits and self-developed code - Have 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.
Required skills
PythonJava