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P

Pardhavi

AI Developer Intern – Data labeling for semantic search

INDIA flag
Hyderabad, India
$10.00/hrIntermediate

Key Skills

Software

No software listed

Top Subject Matter

Multilingual semantic search
information retrieval
knowledge platforms

Top Data Types

TextText
ImageImage

Top Task Types

Fine Tuning
Classification
RLHF
Text Summarization
Red Teaming
Evaluation Rating
Computer Programming Coding
Prompt Response Writing SFT
Question Answering

Freelancer Overview

AI Developer Intern – Data labeling for semantic search. Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Hugging Face and TensorFlow. Education includes Bachelor of Engineering, Stanley College of Engineering and Technology for Women (2026) and Intermediate Certificate, Vishra Junior College (2022). AI-training focus includes data types such as Text, Medical, and DICOM and labeling workflows including Fine-tuning and Classification.

IntermediateEnglish

Labeling Experience

AI Model Evaluator (LLM Evaluation & Annotation)

TextEvaluation Rating
Worked on AI model evaluation and annotation tasks, focusing on assessing and comparing LLM-generated responses based on predefined rubrics. Evaluated outputs for correctness, relevance, coherence, and factual accuracy. Performed side-by-side comparisons, identified reasoning errors, and ensured adherence to quality guidelines. Contributed to improving model performance by providing structured feedback and maintaining consistency across evaluations.

Worked on AI model evaluation and annotation tasks, focusing on assessing and comparing LLM-generated responses based on predefined rubrics. Evaluated outputs for correctness, relevance, coherence, and factual accuracy. Performed side-by-side comparisons, identified reasoning errors, and ensured adherence to quality guidelines. Contributed to improving model performance by providing structured feedback and maintaining consistency across evaluations.

2026 - 2026

AI Developer Intern – Data labeling for semantic search

TextFine Tuning
During the AI Developer Intern role at Swecha, I contributed to the development and training of multilingual retrieval systems utilizing large-scale text, image, and video datasets. My primary responsibility was refining and enhancing model performance using labeled data relevant for rural-access knowledge discovery. I worked closely with Hugging Face models and PyTorch to optimize the accuracy of search and retrieval through iterative model fine-tuning and evaluation. • Curated, prepared, and labeled diverse multilingual datasets for supervised training and validation cycles. • Annotated and structured data to improve semantic search relevance and speed. • Used Python, PyTorch, and Hugging Face as core tooling for model fine-tuning and experimentation. • Collaborated with a cross-functional team to identify labeling bottlenecks and enhance data quality.

During the AI Developer Intern role at Swecha, I contributed to the development and training of multilingual retrieval systems utilizing large-scale text, image, and video datasets. My primary responsibility was refining and enhancing model performance using labeled data relevant for rural-access knowledge discovery. I worked closely with Hugging Face models and PyTorch to optimize the accuracy of search and retrieval through iterative model fine-tuning and evaluation. • Curated, prepared, and labeled diverse multilingual datasets for supervised training and validation cycles. • Annotated and structured data to improve semantic search relevance and speed. • Used Python, PyTorch, and Hugging Face as core tooling for model fine-tuning and experimentation. • Collaborated with a cross-functional team to identify labeling bottlenecks and enhance data quality.

2025 - 2025

Research Intern – Biomedical data labeling and preprocessing

Classification
As a Research Intern at Osmania University, I was responsible for labeling and preprocessing biomedical signal data from patient gait samples. My work involved extracting spatio-temporal features and developing labeled datasets for deep learning classification tasks. These labeled datasets were integral in training CNN-BiLSTM and TCN models to classify patient rehabilitation patterns. • Managed biomedical signal labeling and preprocessing for model training pipelines. • Annotated patient data for supervised gait classification and ensemble learning experiments. • Utilized Python and TensorFlow to engineer, label, and validate datasets for deep-learning workflows. • Enhanced data consistency to enable a macro-AP improvement of 72.5% in model output.

As a Research Intern at Osmania University, I was responsible for labeling and preprocessing biomedical signal data from patient gait samples. My work involved extracting spatio-temporal features and developing labeled datasets for deep learning classification tasks. These labeled datasets were integral in training CNN-BiLSTM and TCN models to classify patient rehabilitation patterns. • Managed biomedical signal labeling and preprocessing for model training pipelines. • Annotated patient data for supervised gait classification and ensemble learning experiments. • Utilized Python and TensorFlow to engineer, label, and validate datasets for deep-learning workflows. • Enhanced data consistency to enable a macro-AP improvement of 72.5% in model output.

2024 - 2024

Education

S

Stanley College of Engineering and Technology for Women

Bachelor of Engineering, Computer Science and Engineering

Bachelor of Engineering
2022 - 2026

Work History

S

Swecha

AI Developer Intern

Hyderabad
2025 - 2025
D

DRDL

Project Intern

Hyderabad
2025 - 2025