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

Amazon· GRAISE (Grocery, Retail & In-Store Experience) / World Wide Grocery Store Tech
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BengaluruFull-timePosted 2w ago

About the role

Applied Scientist to design, develop, and deploy machine learning and computer vision models for the Amazon grocery domain, owning the model development lifecycle from experimentation to deployment and improving the in-store customer shopping experience.

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
  • Own the model development lifecycle from experimentation through deployment — collaborating with software and ML engineers to ensure models meet latency, throughput, and reliability requirements at production scale
  • 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 — analyze model performance from overnight experiments, collaborate with engineers to deploy CV models to production, prototype multimodal approaches with store video and sensor data, present findings to stakeholders, translate results into actionable recommendations
  • About the team — GRAISE builds foundational AI/ML systems powering in-store grocery tech, including models for smart carts, inventory intelligence, personalization, and store operations

Qualifications

  • 2+ years of solving business problems through machine learning, data mining and statistical algorithms experience
  • Experience in designing experiments and statistical analysis of results
  • Experience programming in Java, C++, Python or related language

Skills

Required:Machine learning model developmentComputer visionExperiment design & statistical analysisCommunication with stakeholders
Nice to have:Data pipelines & annotation workflowsProduction deployment
Last updated Oct 25, 2026. Interested? Apply on the company site.

About Amazon

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