Project Manager, Community Feedback Annotation Team at Amazon

Description

• Our overall mission is simple: to be Earth’s most customer-centric company. We want Amazon to be the place where customers can find, discover, and buy anything online. Whatever our customers want, we will find the means to deliver it. With your help, Amazon will deliver world-class AI-generated experiences to our customers.
• At Amazon Community Feedback, we build customer trust through our social and community features. Our Annotation team plays a crucial role in developing and refining AI-powered solutions that enhance these features, powering experiences like Customer Reviews and AI-driven shopping tools.
• We are looking for a Project Manager to coordinate our human-in-the-loop annotation program, which is essential for developing and improving our AI models. In this role, you will manage annotation workflows, drive process improvements, and serve as the bridge between Operations, Science, Engineering, and Business teams. You will lead medium to large-scale projects, ensuring high-quality training data is delivered efficiently and that annotation processes are continuously optimized.
• This role requires a customer-focused approach, data-driven decision-making, and the ability to operate at pace in a complex, cross-functional environment. Your work will directly contribute to developing reliable AI-powered community features that improve customer trust.

Key job responsibilities

AI Model Development & Data Quality

• Manage projects with Annotators and Auditors to deliver quality input data for AI model fine-tuning and evaluation
• Work with stakeholders to forecast project pipelines and align headcount needs
• Collaborate with product and science teams to translate business needs into annotation guidelines
• Oversee data quality and resource allocation to maintain annotation accuracy and efficiency

Process Improvement & Data Analysis

• Identify and implement improvements to annotation process efficiency and quality
• Analyse data to identify trends, root causes, and opportunities for quality improvement
• Drive business and operational metrics through quantitative decision-making and adoption of tools and resources
• Perform deep dives into processes and develop scalable improvement solutions
• Serve as a subject matter expert and referral point for peers and junior team members

Cross-Functional Collaboration & Project Management

• Serve as the primary point of contact between Annotators, Auditors, Science, and Business teams
• Manage medium to large-scale projects bridging Operations, Engineering, Science, and Business teams
• Prioritize projects, manage workflows, and maintain alignment across stakeholders
• Facilitate communication between technical and non-technical teams to ensure shared understanding of requirements and deliverables

A day in the life

• As a Project Manager for the Annotation team, you will orchestrate the provision of high-quality training data and coordinate AI model performance evaluation.
• Your day involves collaborating with annotators, auditors, scientists, product managers, and engineers to manage workflows and drive improvements.
• You will prioritize projects, optimize processes, and ensure alignment across teams — balancing hands-on data quality oversight with strategic project management to enhance annotation efficiency and support the delivery of reliable AI-powered community features.

Basic Qualifications

• Experience with Excel (Pivot Tables, VLookUps) at an advanced level and SQL
• Experience in program or project management
• Experience working cross-functionally with tech and non-tech teams
• Experience defining and implementing process improvement initiatives using data and metrics

Preferred Qualifications

• Experience in driving end to end delivery, and communicating results to senior leadership
• Experience leading process improvements
• Experience in stakeholder management, dealing with multiple stakeholders at varied levels of the organization
• Bachelor's degree or equivalent
• Familiarity with annotation workflows, RLHF labeling standards, or AI model evaluation processes
• Experience with project scheduling, resource planning, and capacity forecasting