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R
Ritwik

Ritwik

Agency

Head of AI Data Worker

India flagPatna, India

Key Skills

Software

AppenAppen
LabelboxLabelbox
CVATCVAT
LabelImgLabelImg
V7 LabsV7 Labs
Surge AISurge AI
RoboflowRoboflow
EncordEncord
SuperviselySupervisely
ArgillaArgilla
SamaSama

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code ProgrammingComputer Code Programming
TextText
AudioAudio

Top Task Types

Bounding BoxBounding Box
Data CollectionData Collection
Computer Programming/CodingComputer Programming/Coding
Red TeamingRed Teaming
RLHFRLHF

Company Overview

Stop wasting weeks on screening calls. Our autonomous AI conducting human-like interviews, scoring candidates on deep technical skills and culture fit, so you can build your elite team overnight.

Security

Security Overview

Our company follows strict security and privacy practices to ensure the protection of client data and intellectual property. All project data is handled through secure access-controlled environments with role-based permissions to ensure that only authorized personnel can access sensitive datasets. We implement strong confidentiality measures including Non-Disclosure Agreements (NDAs) with all team members and partners. Data is stored and processed on secure cloud infrastructure with encryption both in transit and at rest. Access to datasets is logged and monitored to maintain accountability and prevent unauthorized usage. Our annotation workflows are designed to minimize data exposure, and we follow industry best practices for data protection, privacy compliance, and secure handling of AI training datasets. Any sensitive or personally identifiable information (PII) is handled with strict privacy controls.

Labeling Experience

Python-Based Data Processing and Annotation Pipeline for NLP Dataset

Internal/Proprietary ToolingTextTextRLHFRLHFFine-tuningFine-tuning

Our team developed a Python-based data processing and labeling pipeline to prepare high-quality datasets for training Natural Language Processing models. The project involved building automated scripts to collect, preprocess, and structure large volumes of text data before annotation. Python libraries were used for text cleaning, tokenization, and dataset preparation.

Not specified

Automated Text Dataset Labeling Pipeline for NLP Model Training

Internal/Proprietary ToolingTextTextClassificationClassificationEntity (NER) ClassificationEntity (NER) Classification

Our team developed a coding-based data labeling pipeline to prepare training datasets for Natural Language Processing models. The project involved building automated scripts in Python to preprocess, filter, and organize large volumes of text data before annotation. The workflow combined programmatic labeling techniques with human review to ensure high-quality annotations.

Not specified