Industrial Robotics Annotator – Computer Vision Focus

🏢 Lockheed Martin📍 New Port Richey, FL, United States💼 Full-Time💻 On-site🏭 Aerospace and Defense💰 55000-75000 per year

About the Company

Lockheed Martin is a global security and aerospace company that employs approximately 122,000 people worldwide and is principally engaged in the research, design, development, manufacture, integration, and sustainment of advanced technology systems, products, and services. With a strong presence in Florida, we are at the forefront of innovation, including cutting-edge robotics and computer vision applications that enhance security and performance across various domains.

Job Description

We are seeking a detail-oriented and meticulous Industrial Robotics Annotator with a strong focus on Computer Vision to join our advanced technology team in New Port Richey, FL. In this critical role, you will be responsible for accurately labeling and annotating complex datasets derived from industrial robotics operations. Your work will directly contribute to the training and validation of machine learning models that power our next-generation autonomous systems and enhance the precision and safety of robotic movements. This position requires a keen eye for detail, an understanding of spatial relationships, and a basic familiarity with computer vision concepts. Join a team dedicated to innovation and making a significant impact.

Key Responsibilities

  • Perform precise 2D and 3D annotation of image and video data for industrial robotics applications, including object detection, semantic segmentation, and keypoint tracking.
  • Categorize and tag various elements within datasets (e.g., robotic arms, tools, workpieces, environmental features) according to established guidelines and taxonomies.
  • Collaborate closely with AI engineers and data scientists to understand project requirements and refine annotation strategies.
  • Maintain high levels of annotation quality and consistency, adhering to strict data labeling protocols.
  • Provide constructive feedback on annotation tools and guidelines to improve efficiency and accuracy.
  • Identify and escalate data quality issues or ambiguities in the data to relevant stakeholders.
  • Participate in training sessions to learn new annotation techniques and tools as required.

Required Skills

  • Proven experience with data annotation or labeling, preferably in computer vision or machine learning contexts.
  • Strong attention to detail and ability to maintain focus on repetitive tasks.
  • Excellent understanding of spatial reasoning and object recognition.
  • Proficiency with basic computer software and ability to learn new tools quickly.
  • Ability to work independently and as part of a collaborative team.
  • Strong communication skills, both written and verbal.

Preferred Qualifications

  • Bachelor's degree in a related field (e.g., Computer Science, Engineering, Cognitive Science) or equivalent practical experience.
  • Familiarity with common annotation platforms and tools (e.g., Labelbox, VGG Image Annotator, CVAT).
  • Basic knowledge of industrial robotics or automation systems.
  • Experience with 3D point cloud annotation.
  • Exposure to Python scripting for data handling or quality checks.

Perks & Benefits

  • Comprehensive health, dental, and vision insurance plans.
  • Generous paid time off, including vacation, sick leave, and holidays.
  • 401(k) retirement plan with company match.
  • Tuition reimbursement and professional development opportunities.
  • Employee assistance program and wellness initiatives.
  • On-site fitness centers or subsidized gym memberships.
  • Employee discounts on various products and services.
  • Opportunities for career growth in a leading global technology company.

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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