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Amazon Robotics develops state-of-the art robotics for Amazon’s Fulfillment Centers. Come build the future of human-technology interaction with us. We are combining computer vision, mobile robots, advanced end-of-arm tooling, and a high degree of freedom of movement to solve real-world problems on a huge scale. Our team collaborates with a variety of customers across Amazon worldwide to conceive, develop, prototype, and deploy a wide range of robotic systems. Within Amazon Robotics, Global Operations - Artificial Intelligence (GO-AI) enables Amazon to accelerate and scale our machine learning transformation via human-in-the-loop support.

As an Associate, ML Data Operations, you will be a vital Human-in-the-Loop expert in a non-technical role, responsible for executing data annotation tasks across highly diverse portfolios. Your work directly supports the training and validation of machine learning models for Amazon Robotics and Fulfillment Technologies, ensuring the quality and integrity of data which is critical for frontier AI improvements. Your work will involve analyzing processes such as packaging innovation, object manipulation, inventory storage, and sortation automation within fulfillment environments. This role requires strong attention to detail, the ability to make sound judgments using provided resources, and contributes to maintaining fulfillment center quality metrics through precise text/video/image annotation.

Key job responsibilities
This is a non-technical, operational role that requires adhering to process oriented, not programming skills. The Associate will perform precise annotation tasks, adhering to goals for accuracy (quality) and speed (productivity). The candidate is expected to demonstrate:

• Perform precise and consistent annotations across multiple data types (image, video, and text). This includes mastering techniques like object detection, semantic segmentation (pixel-level labeling), object tracking in video, and open-text evaluation.
• Proactively identify and correct errors, ensuring high data integrity and making obsessive precision crucial for model training.
• Leverage strong judgment to address ambiguous situations and, when guidelines fail, propose logical, consistent solutions that contribute to process improvement.
• Quickly learn and efficiently utilize various specialized annotation tools and platforms, adapting to new methodologies as required by evolving programs in domains like packaging, manipulation, storage, and sortation automation.
• Ability to scale and transition between multiple programs based on business needs
• This is a contract position with the potential to transition to a full-time employee role based on business needs.

A day in the life
We are looking for a Associate, ML Data Operations to undertake the task of foundational labelling functions, such as dialogue evaluation on speech, text, audio, and video data. Associates work in a 24x7 environment with rotational shifts. Associates would be working from home (VCC) with a 9-hour shift and with adequate network coverage typically with a reliable ISP (internet >=20 MBPS speed or higher as communicated from time to time) connection, either through DSL or a cable modem. The shift and break timings would be subject to change every 3-4 months or as per business requirement. In case an associate is working in night shift, night shift allowance will be provided as per applicable to Amazon’s work policy.

Associates who are hired to work from home should maintain (1) dedicated workspace i.e., table, chair & sufficient lighting (2) workspace / work related data shouldn’t be accessed by anyone other than employee

Weekly Offs: Rotational two-consecutive days off (it is a 5-day working week with 2 consecutive days off, not necessarily Saturday and Sunday) or as per business discretion.

Training Program: Selected candidates will participate in a structured one-week training program to develop essential capabilities and to ensure operational readiness prior to deployment



Weekly Offs: Rotational two-consecutive day off (it is a 5-day working week with 2 consecutive days off, not necessarily Saturday and Sunday) or as per business discretion.
Basic Qualifications: - Bachelor's degree
- Experience managing time efficiently, meeting personal goals, and working effectively with internal, partner, and customer teams
- •Show willingness to quickly adapt to new annotation methodologies and learn to use various specialized annotation tools
- •Good communication skills with the ability to articulate complex ideas and provide clear explanations.
- •Work in a flexible schedule/shift/work area. Preferred Qualifications: - Work a flexible schedule/shift/work area, including weekends, nights, and/or holidays
- • Experience in data annotation or similar high-volume, quality-focused roles

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