Naman Lal

Key Skills

Software

Other

AWS SageMaker

CrowdSource

Data Annotation Tech

Datasaur

Top Subject Matter

Games - 3D Asset Generation, 2d Asset generation, Game difficulty curve adjustment, Level Generation

Technology & Software - AI assistants, search engines, recommendation systems

Healthcare & Biotechnology - Image Analysis

Top Data Types

Image

Video

Text

Top Label Types

Point Key Point

Segmentation

Classification

Freelancer Overview

I am a Machine Learning Engineer with over 6 years of experience developing AI systems and creating high-quality datasets for training machine learning models across NLP, computer vision, and generative AI. My work has involved designing and curating structured training datasets, including annotated images, segmentation masks, and multimodal datasets used for deep learning pipelines. For example, I built an in-house dataset of sketches paired with 3D models to train reconstruction models and worked with segmentation datasets for defect detection and satellite imagery, where precise labelling and mask generation were critical for model performance. In addition to dataset creation, I have experience evaluating and improving AI model outputs, particularly for large language models and generative systems. My research collaborations and published work in conferences such as CIKM, PAKDD, and IEEE MIPR involve training and benchmarking models on curated datasets, ensuring annotation quality, and validating model outputs. With strong expertise in Python, PyTorch, and large-scale ML pipelines, I bring a combination of technical modelling skills and hands-on experience with AI training data workflows, making me well-suited for tasks involving data labelling, dataset validation, and AI model evaluation.

Labeling Experience

Education

Work History