Spare Parts Tagger – Mechanical AI Focus, Remote

🏢 Amazon Logistics📍 Kahului, HI, United States💼 Full-Time💻 Remote🏭 Logistics & Artificial Intelligence💰 45000-65000 per year

About the Company

Amazon Logistics is at the forefront of global supply chain management, innovating constantly to deliver billions of items to customers worldwide. We leverage advanced technologies, including artificial intelligence and machine learning, to optimize our vast network, improve efficiency, and enhance customer experience. Join a team that values precision, innovation, and global impact.

Job Description

We are seeking a detail-oriented and mechanically inclined Spare Parts Tagger with an AI focus to join our remote team. In this 100% remote role, you will be responsible for accurately identifying, classifying, and tagging mechanical spare parts within our digital inventory systems. You will play a crucial part in training and refining our AI-driven classification models by providing precise data input, ensuring our systems can efficiently manage and locate parts for our extensive operations. This role requires a keen eye for detail, an understanding of mechanical components, and a willingness to engage with AI tools to improve data accuracy and system performance.

Key Responsibilities

  • Accurately identify and categorize a wide range of mechanical spare parts based on established criteria and specifications.
  • Utilize internal software and AI-assisted tools to tag and record detailed information about each part, including part number, description, manufacturer, and usage.
  • Provide feedback and input to improve the performance and accuracy of AI classification algorithms.
  • Conduct quality assurance checks on existing part data to ensure consistency and completeness.
  • Collaborate with engineering and inventory teams to clarify part specifications and resolve discrepancies.
  • Maintain up-to-date knowledge of mechanical components, industry standards, and new part introductions.
  • Document tagging processes and contribute to the creation of best practices for data management.
  • Work independently to meet daily and weekly tagging quotas while maintaining high standards of accuracy.

Required Skills

  • Strong mechanical aptitude and ability to identify various mechanical components (e.g., gears, bearings, fasteners, electrical components).
  • Exceptional attention to detail and accuracy in data entry and classification.
  • Proficiency with computer systems, database software, and comfortable learning new digital tools.
  • Basic understanding of AI/Machine Learning concepts and willingness to work with AI-driven systems.
  • Excellent organizational and time management skills to handle multiple tasks in a remote environment.
  • Effective written and verbal communication skills in English.
  • Ability to work independently and maintain focus in a remote work setting.

Preferred Qualifications

  • 1+ years of experience in inventory management, parts department, or a related field.
  • Familiarity with CAD software or Product Information Management (PIM) systems.
  • Experience in an e-commerce or logistics environment.
  • Certifications or vocational training in mechanical engineering, automotive, or industrial maintenance.
  • Proven ability to adapt to evolving technologies and processes.

Perks & Benefits

  • Comprehensive health, dental, and vision insurance.
  • Paid time off and holidays.
  • 401(k) plan with company match.
  • Employee assistance program.
  • Opportunities for professional development and career growth.
  • Work-from-home stipend for essential office equipment and internet.
  • Employee discounts on Amazon products and services.

How to Apply

If you are interested in this position, please click the "Apply Now" button below. To ensure your application is properly considered, please prepare the following:

  • An up-to-date Resume or CV
  • A brief cover letter summarizing your experience and motivation

Applications are reviewed on a rolling basis. Only shortlisted candidates will be contacted for an interview.

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