Manoj Kumar

Detail-oriented Data Annotation Specialist with 1 year of professional experience in 2D image annotation and 3D LiDAR video annotation, plus 5 months of freelance data annotation experience from May–September 2026. Skilled in image classification, bounding box and polygon annotation, segmentation, object detection and tracking, point-cloud labelling, LLM response evaluation, content categorization, multilingual data projects, and QA/QC validation. Experienced in PII/document validation and AI/ML training-data workflows with strong accuracy, guideline compliance, and attention to edge cases.

Freelance Data Annotator | RAI/LLM Content & PII/Privacy Annotation - Freelance

(2026-05 - 2026-09)

• Performed dual-track annotation for a Responsible AI content-safety and privacy-protection initiative, spanning harmful-content labelling and PII detection across multilingual, multi-domain text.
• Classified prompt/completion pairs across six harm categories (Misconduct, Violence, Hate, Stereotype, Insults, Sexual) following a structured, version-controlled SOP.
• Scored each item on intent (harmful/harmless/unspecified), intensity (low/medium/high/hard-to-decide), a 0–5 severity scale, and a 0–4 confidence rating, applying nuanced rules for multi-label harms, profanity vs. insult distinctions, and edge cases (incomplete text, multilingual content, text-processing requests).
• Delivered labels in a standardized output format to maintain consistency across a distributed annotation team.
• Annotated PII with character-exact span offsets across healthcare records, benign look-alike data (for false-positive-rate reduction), long-context documents requiring coreference resolution, and structured data (JSON/XML/HTML).
• Applied 15+ canonical PII entity types with locale-specific variants (US, UK, Canada, India, international) and delivered output in structured JSONL format meeting >95% annotation-accuracy QA standards.
• Incorporated iterative client feedback to improve span accuracy, adopt newly introduced entity tags, and increase realism of document/conversation samples.

Data Annotator - Adept Talent Acquisition Pvt Ltd

(2025-05 - 2026-05)

• Executed 2D and 3D annotation tasks for autonomous driving, logistics, and mapping datasets.
• Created accurate labels for vehicles, pedestrians, traffic signs, speed limits, stop boards, curbs, medians, and road edges.
• Performed sensor fusion alignment between camera and LiDAR data for precise localization.
• Maintained high accuracy and consistency while meeting daily productivity targets.
• Supported QA teams by reviewing annotations and correcting errors.
• Daily annotated and validated 1000+ 3D LiDAR point cloud frames and objects (vehicles, pedestrians, cyclists, road infrastructure) using 3D bounding boxes and cuboids with a 98.5% QA accuracy rate.
• Placed and adjusted accurate 3D bounding cuboids for dynamic road users (vehicles, pedestrians) with strict adherence to project ground-truth rules.

Bachelor of Technology - B. Tech - Annamacharya Institute of Technology & Sciences, Tirupati (AITS-T) (2016)