Neeraj Tiwari

Key Skills

Software

Appen

Clickworker

CVAT

Labelbox

Playment

Scale AI

Surge AI

Toloka

Telus

Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Audio

Document

Image

Text

Video

Top Label Types

Action Recognition

Audio Recording

Bounding Box

Classification

Diagnosis

Evaluation Rating

Object Detection

Point Key Point

Prompt Response Writing SFT

Red Teaming

RLHF

Segmentation

Text Generation

Text Summarization

Tracking

Transcription

Translation Localization

Freelancer Overview

I am a multilingual language quality evaluator and translation specialist with extensive experience in data annotation and AI training data for NLP applications. With native-level proficiency in Thai, Korean, Hindi, and Gujarati, as well as advanced English and Japanese skills, I excel at evaluating machine-translated content, assessing semantic equivalence, and ensuring linguistic accuracy across multiple languages. I am adept at following detailed annotation guidelines, providing clear qualitative feedback, and conducting linguistic analysis to enhance data quality. My background in literature, writing, and editing enables me to deliver high-quality, guideline-based evaluations and annotations for diverse projects, supporting the development of robust AI language models.

Labeling Experience

Medical Image Annotation for Healthcare Diagnostics

Internal Proprietary ToolingImagePoint Key PointText Summarization

Annotation by trained specialists marking anatomical features and pathological indicators (tumors, fractures) in medical imaging. This high-precision labeled dataset was used to train diagnostic AI systems for clinical research.

Annotation by trained specialists marking anatomical features and pathological indicators (tumors, fractures) in medical imaging. This high-precision labeled dataset was used to train diagnostic AI systems for clinical research.

2024

Vehicle Object & Lane Annotation for Self-Driving Training

CVATImageBounding BoxSegmentation

Coordinated labeling of large driving datasets including cars, pedestrians, road signs, and lane markers for improving computer vision systems in autonomous vehicles. This project enhanced object detection and scene understanding model performance.

Coordinated labeling of large driving datasets including cars, pedestrians, road signs, and lane markers for improving computer vision systems in autonomous vehicles. This project enhanced object detection and scene understanding model performance.

2023 - 2024

Solar Panels & Regulatory Document Annotation Projects

LabelboxImageSegmentationClassification

The Label Your Data team annotated thousands of photos to detect solar panels and related infrastructure, and separately labeled tens of thousands of regulatory document texts for classification tasks. This supported solar inspection analytics and legal document indexing in NLP workflows.

The Label Your Data team annotated thousands of photos to detect solar panels and related infrastructure, and separately labeled tens of thousands of regulatory document texts for classification tasks. This supported solar inspection analytics and legal document indexing in NLP workflows.

2022 - 2023

Surge AI Human Feedback & Language Annotation

Surge AITextRLHFPrompt Response Writing SFT

Surge AI worked with large language model developers to label AI outputs and provide human feedback, improving model alignment and quality of generative systems. Tasks included ranking model responses, annotating errors, and providing contextual corrections for text.

Surge AI worked with large language model developers to label AI outputs and provide human feedback, improving model alignment and quality of generative systems. Tasks included ranking model responses, annotating errors, and providing contextual corrections for text.

2020 - 2022

Scale AI / Remotasks Vision Labeling Work

Scale AI3D SensorSegmentationObject Detection

A large distributed labeling workflow used by Scale AI’s Remotasks community to annotate complex vision data (frames, sensor imagery) for training self-driving and perception systems. Includes high-volume micro-tasks broken into object bounding boxes, category tags, and sequential scene labeling.

A large distributed labeling workflow used by Scale AI’s Remotasks community to annotate complex vision data (frames, sensor imagery) for training self-driving and perception systems. Includes high-volume micro-tasks broken into object bounding boxes, category tags, and sequential scene labeling.

2018 - 2019

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Education

Work History