Process Lead, Core Shopping

Amazon· Corporate Operations
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📍 Bengaluru, Karnataka, INDfull time
Machine Learning Data Operatioconsumer_engagement

About this role

Core Shopping Operations strives to become the most reliable source for dataset generation and annotations. We work in collaboration with Shopping feature teams to enhance customer experience (CX) quality across shopping features, devices, and locales. Our primary focus lies in handling annotations for training, measuring, and improving Artificial Intelligence (AI) and Large Language Models (LLMs), enabling Amazon to deliver a superior shopping experience to customers worldwide. Our mission is to empower Amazon's LLMs through Reinforcement Learning from Human Feedback (RLHF) across various categories at high speed. We aspire to provide an end-to-end data solution for the LLM lifecycle, leveraging pioneering technology alongside our operational excellence. By joining us, you will play a pivotal role in shaping the future of the shopping experience for customers worldwide.

Key job responsibilities
The candidate actively seeks to understand Amazon’s core business values and initiatives, and translates those into everyday practices.
Some of the key result areas include, but not limited to:
· Experience in managing process and operational escalations
· Driving appropriate data oriented analysis, adoption of technology solutions and process improvement projects to achieve operational and business goal
· Managing stakeholder communication across multiple lines of business on operational milestones, process changes and escalations
· Communicate and take the lead role in identifying Gaps in process areas and work with all stakeholders to resolve the gaps
· Be a SME for the process and a referral point for peers and junior team members
· Has the ability to drive business/operational metrics through quantitative decision making, and adoption of different tools and resources
· Ability to meet deadlines in a fast paced work environment driven by complex software systems and processes
· Ability to perform deep dive in the process and come up with process improvement solutions through automation
· Shall collaborate effectively with other teams and subject matter experts (SMEs), Language Engineers (LaEs) to support launches of new process and services

About the team
Core Shopping Operations strives to become the most reliable source for dataset generation and annotations. We work in collaboration with Shopping feature teams to enhance customer experience (CX) quality across shopping features, devices, and locales. Our primary focus lies in handling annotations for training, measuring, and improving Artificial Intelligence (AI) and Large Language Models (LLMs), enabling Amazon to deliver a superior shopping experience to customers worldwide. Our mission is to empower Amazon's LLMs through Reinforcement Learning from Human Feedback (RLHF) across various categories at high speed. We aspire to provide an end-to-end data solution for the LLM lifecycle, leveraging pioneering technology alongside our operational excellence. By joining us, you will play a pivotal role in shaping the future of the shopping experience for customers worldwide.

Basic qualifications

- Bachelor's degree or equivalent
- Experience in process improvement/quality control tools and methods
- Experience collaborating with cross-functional teams
- Experience in English-language communication skills, both written and verbal
- Experience working in a fast-paced, rapidly changing operations environment
- Experience in defining and implementing process improvement initiatives using data and metrics
- Bachelor's degree or equivalent
- Analyze and interpret complex Standard Operating Procedures (SOPs) to ensure organizational adherence.
- Demonstrate excellent problem-solving skills with proactive identification of process improvement opportunities.
- Drive cross-functional optimization efforts that deliver measurable operational excellence.

Preferred qualifications

- Knowledge of CSV, JSON, Markdown or python
- Knowledge of machine learning models

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.

Frequently Asked Questions

Is the salary disclosed for the Process Lead, Core Shopping position at Amazon?
The salary for this Process Lead, Core Shopping role at Amazon is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Process Lead, Core Shopping position at Amazon located?
This Process Lead, Core Shopping role at Amazon is based in Bengaluru, Karnataka, IND. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the Process Lead, Core Shopping role at Amazon full-time or part-time?
This is listed as a full time position. It is posted as a Process Lead, Core Shopping role in the Corporate Operations department at Amazon.
Which team or department does the Process Lead, Core Shopping at Amazon belong to?
This Process Lead, Core Shopping position is part of the Corporate Operations department at Amazon. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Process Lead, Core Shopping position at Amazon?
Click the "Apply Now" button on this page. You will be redirected to Amazon's official application portal hosted on amazonjobs where you can submit your application directly.
When was the Process Lead, Core Shopping job at Amazon posted?
This Process Lead, Core Shopping position at Amazon was posted on Sep 17, 2026. Apply as soon as possible — early applications are often reviewed first.
Process Lead, Core Shopping
Amazon
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