Deepjit D.

Key Skills

Software

Scale AI

Top Subject Matter

Extreme climate events and spatiotemporal rainfall forecasting

GenAI (RAG)

data science

Top Data Types

Text

Top Task Types

Function Calling

Prompt + Response Writing (SFT)

Classification

Freelancer Overview

Senior Machine Learning Researcher (IISER Pune) — end-to-end ML pipeline development for scientific forecasting and reas. Brings 9+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and LangChain. Education includes Bachelor of Science and Master of Science, Indian Institute of Science Education and Research (IISER), Pune (2022) and High School Certificate, Bharatiya Vidya Bhavan, Agartala (2017). AI-training focus includes data types such as Text and labeling workflows including Function Calling,

Labeling Experience

Senior Machine Learning Researcher (IISER Pune) — end-to-end ML pipeline development for scientific forecasting and reasoning-chain workflows

TextFunction Calling

Developed deterministic ML models and automated high-dimensional data processing pipelines for scientific forecasting, including reasoning-chain workflows for spatiotemporal organization of rainfall data. Built and optimized simulation and forecasting workflows on HPC infrastructure where intermediate structured outputs support model training and evaluation. Applied LLM/RAG-style retrieval and reasoning concepts to support complex scientific problem solving and downstream model use cases. • Created reproducible training and forecasting pipelines for extreme climate event modeling • Automated data preprocessing using Python, Xarray, and NumPy for model-ready datasets • Optimized Slurm-based workloads for large-scale scientific simulation runs • Designed reasoning-chain requirements for complex forecasting tasks

2020 - Present

ML Solutions Architect (GenAI & Data Science) — RAG-based insight extraction and evaluation problem design

TextPrompt + Response Writing (SFT)

Architected GenAI solutions using RAG to automate insight extraction from technical repositories for educational and scientific use cases. Implemented MLOps practices for model deployment and validation to ensure scalable performance across diverse scientific domains. Designed evaluation-oriented STEM problems with statistical rigor that can be used to label or assess model outputs. • Built RAG pipelines using LangChain and vector databases (ChromaDB/Pinecone mentioned elsewhere) • Implemented deployment/validation workflows aligned with MLOps best practices • Designed original STEM problems for educational evaluation and computational complexity • Produced systems to convert repository content into structured answers/insights

2019 - 2020

Machine Learning Intern (Computational Biology) — biomarker discovery and verification

TextClassification

Performed computational biology transcriptomic analysis to discover ovarian cancer biomarkers using statistical modeling with Python. Validated complex biological findings with SciPy and scikit-learn, supporting downstream therapeutic target identification workflows. Contributed to verification steps that effectively label/confirm biomarker candidates for research outputs. • Applied statistical modeling to identify candidate biomarkers from transcriptomic data • Used SciPy and scikit-learn to verify biological solution outputs • Supported therapeutic target identification through validated biomarker insights • Worked on computational workflows that generate labeled research findings

2018 - 2018

Education

Work History