Priyanshu G.

Key Skills

Software

Appen

Axiom AI

Clickworker

Labelbox

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Video

Top Task Types

Audio Recording

Bounding Box

Classification

Prompt + Response Writing (SFT)

Text Generation

Freelancer Overview

Aspiring Data Scientist and Machine Learning enthusiast with strong foundations in C++, JavaScript, Python, SQL, and MongoDB. Skilled in data preprocessing, analysis, and visualization, with hands-on experience in backend development (Node.js, Express) and authentication systems (JWT, bcrypt). Currently exploring Machine Learning algorithms, Natural Language Processing, and Large Language Models (LLMs) with the goal of building scalable AI-driven applications. Passionate about applying data-driven insights to solve real-world problems and leveraging LLMs for intelligent automation, information retrieval, and conversational AI. Key Interests: Data Engineering | Machine Learning | NLP | LLM Fine-Tuning | AI Applications

Labeling Experience

Data Annotator

LabelboxTextQuestion Answering

Utilized Labelbox to create and manage large-scale data annotation projects for computer vision and NLP tasks. Designed custom labeling workflows including classification, object detection, segmentation, and text annotation to ensure high-quality labeled datasets. Collaborated with annotators and reviewers to establish quality control pipelines, reducing labeling errors and improving dataset reliability. Integrated Labelbox with Python SDK and APIs to automate data ingestion, annotation exports, and feedback loops. Applied active learning strategies by iteratively training models and sending edge cases back for annotation, significantly enhancing dataset efficiency. Leveraged Labelbox model-assisted labeling to speed up annotation throughput and reduce manual effort. Documented and streamlined the end-to-end pipeline from raw data → annotation → model training → evaluation for reproducibility. Tech Stack: Labelbox, Python, TensorFlow/PyTorch, OpenCV, Pandas, NumPy

2024 - 2025

Prompt Engineer

Scale AIComputer Code ProgrammingQuestion Answering

Designed, tested, and optimized prompts for Large Language Models (LLMs) to improve response accuracy, reliability, and task-specific performance. Conducted prompt chaining, few-shot learning, and role-based prompting to enhance contextual understanding and reduce hallucinations. Developed custom LLM-powered applications for tasks such as summarization, code generation, data extraction, and knowledge retrieval. Built evaluation pipelines to measure LLM output quality (relevance, coherence, factual accuracy) using both human feedback and automated metrics. Explored and implemented fine-tuning techniques and retrieval-augmented generation (RAG) for domain-specific tasks. Collaborated with backend systems to integrate LLM APIs (e.g., OpenAI, Hugging Face models) into full-stack applications. Researched and documented best practices in AI safety, bias mitigation, and ethical prompt design. Tech Stack: Python, Node.js, LangChain, OpenAI API, Hugging Face, MongoDB, SQL

2024 - 2025

Education

Work History