ML Data Operations Associate – Amazon (Remote, Full-Time)

📅 Posted: April 6, 2025
🕒 Apply ASAP – Limited Openings Available in the U.S.
🌎 Remote | Full-Time | Contract (6 months)

🔍 About the Role: Associate, ML Data Operations – GO-AI at Amazon

Amazon is hiring for a remote Associate role in ML Data Operations under its GO-AI division. This position is critical in automating fulfillment center operations using human-in-the-loop video and image data auditing. As an Associate, you’ll be responsible for reviewing short-stowing action videos from Amazon Robotics Fulfillment Centers and using human judgment to annotate or verify product placements.

This 6-month contract role is ideal for detail-oriented professionals who can work independently, follow accuracy and productivity metrics, and contribute to AI training processes through manual video verification.

🧠 What is GO-AI at Amazon?

GO-AI (Global Operations—Artificial Intelligence) is Amazon’s initiative to improve automation and robotics in its fulfillment network. This team supports Amazon’s Fulfillment Technologies and robotics by enabling machine learning models through human-audited data inputs.

Key goals of the GO-AI operations team include:

• Improving store quality through precise product-location validation

• Enhancing machine learning models via high-accuracy human audit data

• Supportingthe  AI pipeline with image/video annotation for better automation

👤 Meet the Hiring Organization: Amazon

🔗 View Amazon on LinkedIn

Amazon is a global leader in e-commerce, cloud computing, AI, and robotics. With over 1 million employees, Amazon continues to pioneer technologies that shape the future of logistics, customer experience, and intelligent automation. This role is based in the ADCI (Amazon Development Center India) division under the Karnataka – A66 business unit, but is open to U.S. candidates working remotely.

🛠️ Day-to-Day Responsibilities

As an ML Data Operations Associate, you will:

• Review 15–20 second videos showing product storage actions

• Annotate or verify product locations in the system usingthe  provided tools

• Follow detailed SOPs to maintain data labeling accuracy and consistency

• Meet daily and weekly productivity and quality goals

• Follow structured break schedules to ensure workflow efficiency

• Work 6.8 to 7 hours actively per day within a 9-hour shift

• Maintain a dedicated remote workspace (lighting, desk, chair required)

• Turn on the laptop camera during scheduled virtual meetings

🧩 Role Structure & Schedule

✅ Candidate Requirements

Basic Qualifications

• Bachelor’s degree from an accredited institution

• Ability to stay focused and alert for prolonged video analysis

• High level of accuracy, speed, and attention to detail

Preferred Qualifications

• Flexible with shift timings and weekend/holiday work

• Experience in non-technical data annotation or auditing

• Willingness to work under tight deadlines and productivity targets

• Comfortable with remote team collaboration and digital tools

💡 Why This Role Matters

This position supports Amazon’s mission to automate fulfillment centers by providing clean, annotated datasets for machine learning models. Your contributions will:

• Improve product placement accuracy

• Enhance robotic decision-making

• Reduce defects in inventory management

• Enable more innovative stowing systems in Amazon warehouses

🖥️ Required Remote Work Setup

To qualify for this remote role, candidates must maintain:

• A dedicated home workspace with a table, chair, and good lighting

• Data security protocols (no shared access to work-related materials)

• Stable internet and readiness for webcam-based virtual meetings

💼 About the Team: GO-AI Data Auditing Operations

The Data Auditing Ops team reviews short-form stowing videos to support fulfillment accuracy. These videos are annotated to train AI agents to track, validate, and respond to inventory movements autonomously. The annotated data improves the automation pipeline in Amazon’s AI-enabled warehouse environments.

📩 How to Apply

👉 Apply Now on LinkedIn
Position ID: A2946954

To increase your chances of selection, make sure your profile includes relevant data operations, attention to detail, and video/image analysis experience.