Shubhankar Sharma

Machine Learning Engineer

https://www.opentalent.in/shubhankar-sharma

Machine Learning Engineer with less than a year in NLP/LLM engineering, computer vision, and full-st

Key Strengths

Strong foundational knowledge in Machine Learning and Deep Learning, evidenced by projects involving CNNs, XGBoost, and TensorFlow.
Extensive experience in building and deploying end-to-end ML systems, including FastAPI backends and Streamlit/React frontends.
Proficiency in LLM engineering, agentic workflows, and local LLM integration for tasks like content generation and job application automation.
Demonstrated ability to optimize ML models and systems for resource-constrained environments (e.g., 6 GB VRAM GPU optimization).
Good understanding of MLOps principles, including deployment on platforms like Hugging Face Spaces and Vercel, and real-time monitoring dashboards.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's portfolio showcases a strong passion for AI/ML and automation, aligning well with an innovative and fast-paced technical culture. The diversity of personal projects, from plant disease detection to autonomous content pipelines and job application systems, indicates a broad interest in applying ML to various real-world problems. The ongoing M.Sc. in Mathematics & Computing further supports a commitment to continuous learning and academic rigor. The lack of professional experience makes it challenging to assess cultural fit beyond technical alignment.

Soft Skills & Operational Fit

The candidate demonstrates strong problem-solving skills through complex project implementations and a proactive approach to learning new technologies. The focus on autonomous systems and optimized architectures suggests an independent and efficient work style. However, without direct work experience or psychometric test results, it's difficult to assess stress handling, team collaboration, or communication clarity in a professional setting.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

About

Data Scientist and AI Developer with extensive experience in NLP/LLM engineering and computer vision. Skilled in designing automated pipelines and agentic workflows to solve complex operational challenges. Hands-on experience migrating legacy models to modern cloud spaces and resolving integration hurdles in production environments. Committed to developing innovative, data-driven products that utilize cutting-edge deep learning frameworks and automation protocols.

Top Skills

PythonStatisticsTensorFlowPyTorchFastapi

Projects

Agentic Job Application Pipeline

June 1, 2025 – Present

Built an end-to-end autonomous pipeline targeting LinkedIn and Naukri, automating job discovery, resume-JD semantic matching, and one-click application submission. Implemented semantic similarity scoring using Ollama-embedded local LLMs for resume-JD relevance ranking. Orchestrated multi-step agentic workflows via LangGraph with Playwright-driven browser automation and anti-detection capabilities. Developed a Streamlit-based real-time tracking dashboard with persistent application state monitoring.

View Project

Fraud Shield - Deployed ML-Driven Fraud Detection System

June 1, 2025 – Present

Engineered an end-to-end fraud detection system featuring a FastAPI backend (deployed on Hugging Face Spaces) and a React frontend (deployed on Vercel). Integrated high-performance XGBoost and TensorFlow models to provide real-time risk scoring and mitigate fraudulent transactions with high precision. Developed an interactive dashboard for live monitoring and feature-level explainability, bridging the gap between complex ML outputs and actionable business insights.

Full-Stack Web Applications – Luminary | Wipsom | Top Avenue

June 1, 2025 – Present

Luminary: developed a production-grade social platform with real-time chat (Socket.io), JWT authentication on Next.js 14 and Express. Wipsom: engineered a full-featured e-commerce and productivity platform with end-to-end user flows. Top Avenue: designed and deployed a responsive, full-stack web application tailored for hospitality, streamlining user interactions and digital workflows.

Automated YouTube Content Pipeline - Local LLM System

June 1, 2025 – Present

Engineered an 8-agent autonomous system that handles trend research, script generation, voiceovers, visual asset fetching, and full video assembly without human intervention. Optimised architecture for a 6 GB VRAM GPU by stripping heavy abstractions, implementing strict GPU garbage collection, and using native FFmpeg subprocesses for crash-free rendering. Built a real-time management dashboard with persistent state recovery using FastAPI backend and SQLite state management. Integrated Groq LLM for fast inference, local OpenAI Whisper for transcription, and edge-tts for neural voiceover generation.

Plant Disease Detection System

June 1, 2025 – Present

Designed and trained a CNN-based image classification model to detect plant diseases from leaf images using labeled datasets with preprocessing and data augmentation techniques. Achieved strong multi-class classification performance across multiple disease categories with optimised model architecture. Deployed the model as an interactive Streamlit web application, enabling users to upload leaf images and receive real-time disease predictions.

View Project

Key Strengths

Strong foundational knowledge in Machine Learning and Deep Learning, evidenced by projects involving CNNs, XGBoost, and TensorFlow.
Extensive experience in building and deploying end-to-end ML systems, including FastAPI backends and Streamlit/React frontends.
Proficiency in LLM engineering, agentic workflows, and local LLM integration for tasks like content generation and job application automation.
Demonstrated ability to optimize ML models and systems for resource-constrained environments (e.g., 6 GB VRAM GPU optimization).
Good understanding of MLOps principles, including deployment on platforms like Hugging Face Spaces and Vercel, and real-time monitoring dashboards.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Shubhankar Sharma

Key Strengths

Cultural & Operational Fit

About

Top Skills

Skills

Education

Projects

Certifications

Key Strengths

Cultural & Operational Fit