Siddhant S.

Key Skills

Software

Google Cloud Vertex AI

Top Subject Matter

Library recommendations and AI model integration

Ecotherapy and sustainability project operations

Legal Services & Contract Review

Top Data Types

Text

Audio

Document

Top Task Types

Function Calling

Data Collection

Freelancer Overview

Open Library AI Project (Computer Science NEA) - AI integration and recommendation engine development. Brings 2+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Google Cloud Vertex AI. Education includes A-Level, N/A (2026) and GCSE, N/A (2024). AI-training focus includes data types such as Computer Code, Programming, and Text and labeling workflows including Function Calling and Data Collection.

Labeling Experience

Horticultural Volunteer – Ecotherapy & Sustainability Project

TextData Collection

Performed observational and maintenance support tasks within a community-focused sustainability setting. While this role was not an explicit AI training or labeling position, it involved systematic recording/handling of project materials following structured procedures. This experience reflects reliability and attention to detail that can transfer to annotation or data collection workflows. • Execute environmental maintenance tasks using systematic, multi-step instructions • Maintain organizational consistency within a community-focused project • Manage physical equipment and ensure procedural adherence • Support structured activity execution that emphasizes accurate, repeatable processes

2025 - Present

Open Library AI Project (Computer Science NEA) - AI integration and recommendation engine development

Google Cloud Vertex AIFunction Calling

Worked on a full-stack Open Library AI project where AI models were integrated into an application using data-filtering algorithms. Focus included preparing and connecting model inputs/outputs within the system workflow rather than manual annotation of images or text datasets. The work supported recommendation-style behavior by leveraging structured data from an SQL backend. • Integrated Google AI models via Google AI Studio and a recommendation engine workflow • Implemented data-filtering algorithms to drive model-based recommendations • Built and connected an SQL database backend for library application data • Authored comprehensive technical documentation for the project

2025 - 2026

Education

Work History