Associate II, ML Data Operations, GO-AI Operations

About the Role

Amazon Robotics develops state-of-the-art robotics for Amazon’s Fulfillment Centers. This is a non-technical operational role focused on human-in-the-loop support to accelerate and scale machine learning transformation. As an Associate II, ML Data Operations, you will be a vital expert responsible for executing data annotation tasks. 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 for AI improvements. This role is offered on a contractual basis, with the opportunity to transition into a full-time position based on performance and business requirements.

Key Responsibilities

• Deliver high-quality training data to improve and expand Large Language Model (LLM) capabilities.
• Perform precise annotation tasks (labeling or tagging data for machine learning training).
• Display flexibility with the ability to transition immediately between projects as per business requirements.
• Proactively identify day-to-day operational friction and bottlenecks within Standard Operating Procedures (SOPs) and tools, proposing logical conclusions and actionable changes to unblock workflows.
• Perform precise and consistent annotations across multiple data types: image, video, and text.
• Master techniques like object detection, semantic segmentation, object tracking in video, and open-text evaluation.
• Proactively identify and correct errors, ensuring high data integrity.
• Write grammatically correct, creative, and technical texts in various styles, strictly adhering to complex project guidelines.
• Make strong judgments to address ambiguous situations or incomplete information and propose logical, consistent solutions when guidelines fail.
• Quickly learn and efficiently utilize various specialized annotation tools and platforms, adapting to new methodologies.
• Scale and transition between 2-3 programs based on business needs.
• Train associates and provide peer feedback.
• Validate data based on specific annotation guidelines, ensuring accuracy and quality.
• Strive to enhance the productivity and effectiveness of data generation by contributing to the development and continuous improvement of audit methodologies, checklists, and test frameworks.
• Undertake foundational labeling functions, such as dialogue evaluation on speech, text, audio, and video data.
• Collaborate with a diverse team of specialists, sharing insights on "edge cases" where data is ambiguous.

Requirements & Tech Stack

• Data Transcription and Annotation experience.
• Specializing in LLM annotation work using Amazon internal generative AI tools.
• Experience in natural language data labeling, data annotation, linguistic annotation, or other forms of data markup.
• Experience with computer skills, including proficiency in MS Office (Word, Excel, PowerPoint).
• Ability to write basic prompts to gather and synthesize information from multiple sources.
• Ability to work in a flexible schedule/shift/work area, including weekends, nights, and/or holidays.
• Work in a 24x7 environment with rotational shifts (9-hour shifts).
• Night shift allowance will be provided for night shifts as per Amazon’s work policy.
• Rotational two-consecutive days off (5-day working week).
• Participate in a structured one-week training program.

Qualifications

• Bachelor’s degree in any discipline.
• English proficiency (C1+ or > C1 fluency) with good business writing skills.
• Demonstrate proficiency in generating high-quality human insight data across a range of modalities, inclusive of text, image, video, and audio.
• Excellent organizational and time management skills to prioritize complex tasks effectively.
• Comfortable working in a collaborative environment with remote, multi-cultural teams, willing to share knowledge, and able to maintain individual productivity goals.
• Good communication skills with the ability to articulate complex ideas and provide clear explanations.
• Strong concentration and effective multitasking skills.
• Familiarity with writing basic prompts.
• Ability to dive deep into use cases and interpret and implement solutions.
• The shift and break timings would be subject to change every 3-4 months or as per business requirement.