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Nami Kim

Nami Kim

Robotics Data Quality Coordinator

Talente
MunichMitglied seit 18. Mai 2026
Python
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Python

Über

Munich-based robotics data quality candidate with direct teleoperation exposure at Agile Robots and two years of regulated physical-systems inspection and coordination experience at Egis. Comfortable checking execution against a defined standard, documenting deviations so they stay reviewable, and keeping engineers, field teams, and reviewers aligned on what happens next. Focused on turning recurring data-quality issues into clearer SOPs, sharper operator coaching, and visible trends, not just a longer list of flagged rows.

Berufserfahrung

Robotics Operations / Teleoperation Support at Agile Robots SE (2026-03 – 2026-04)

  • Gained direct operator-side exposure to robotics data collection and task execution in a structured teleoperation environment.
  • Followed task procedures, status updates, equipment-readiness routines, and handoff practices around robot operations.
  • Built practical insight into how operator consistency and reviewable records shape robotics training data quality.

Heavy Civil Inspector / Contract Administration Support at Egis, formerly McIntosh Perry (2021-01 – 2023-12)

  • Tracked 100,000+ tonnes of mixed materials across $50M+ in public infrastructure projects, with full delivery evidence on record.
  • Checked regulated physical work against drawings, specifications, and acceptance conditions across multiple active work fronts.
  • Documented deviations, material records, photographs, and handoff evidence for responsible review.
  • Communicated findings and next actions between engineers, contractors, and field teams while preserving decision boundaries.

Robot Teleoperation Data Audit Lab at Independent Python project (2026-04 – 2026-06)

Independent Python project, github.com/Nami3777/robot-teleop-data-audit

  • Built a Python pre-training triage tool for LeRobot-style teleoperation episodes, classifying each as pass, review, or flag before training.
  • Implemented checks for incomplete or unusually long episodes, timestamp gaps, and repeated or stuck actions.
  • Added configurable task and SOP thresholds, with reviewable CSV and Markdown reports.

Ausbildung

M.Sc. in Data Science – University of Europe for Applied Sciences (2025-09 – 2025-09)

Diploma in Construction Engineering Technology – Algonquin College (2021-01 – 2021-12)

Fähigkeiten

Robotics Data Quality Coordinator

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