Sasi Sundar

Building end-to-end AI/ML systems with Python, LLMs, and modern interface tooling.

I’m an AI/ML student researcher developing end-to-end Python pipelines and building practical experience with LLMs, agents, RAG, and MCP as I advance toward deeper expertise. I’ve delivered over fifteen ML and LLM projects covering data processing, model training, evaluation, and deployment-ready serving. My workflows are reproducible through Dockerized environments and CI/CD. I work effectively with GenAI and prompt engineering, and I learn new technologies at high speed, enabling fast iteration from concept to functioning system. My focus is mastering the full lifecycle of modern AI systems and growing into robust agentic and reasoning-centered architectures.

Technical Competencies

AI/ML Engineering

  • Machine learning: supervised, unsupervised, feature engineering, and model evaluation.
  • Deep learning with PyTorch and TensorFlow for image, text, and sequence models.
  • LLMs, prompt engineering, LangChain, RAG, and function-calling workflows.
  • Agentic pipelines with multi-step reasoning and tool integration.
  • NLP: embeddings, tokenization, preprocessing, and classic NLP techniques.
  • Computer vision with OpenCV and custom preprocessing.
  • Python data stack: NumPy, Pandas, quantitative analysis.

Backend, APIs, and Systems

  • Python for backend development and ML system orchestration.
  • FastAPI and Flask for REST services and model serving.
  • JavaScript, TypeScript, Node.js, Express.js for backend web services.
  • API design: routing, async flows, and ML/LLM inference endpoints.
  • Integration of OpenAI and other LLM APIs.

Cloud, DevOps, and MLOps

  • AWS and Google Cloud for compute, deployment, and service orchestration.
  • Docker for reproducible, containerized ML/LLM environments.
  • Kubernetes fundamentals for orchestration workflows.
  • CI/CD with GitHub Actions for automated builds and deployments.
  • Databases: SQL (MySQL, PostgreSQL), MongoDB, Firebase.
  • MLOps: versioning, environment management, deployment automation.

Frontend and Interface Engineering

  • React.js for interactive dashboards, admin panels, and ML tooling interfaces.
  • ADK for relevant application development workflows.

Software Engineering Foundations

  • Data structures and algorithms for performance-oriented problem solving.
  • Git and GitHub for version control and collaborative development.
  • Agile development practices, debugging workflows, and code quality standards.

Selected Projects

End-to-end AI/ML and LLM systems I’ve designed, implemented, and deployed.

Procurement Agent System

LLM Procurement Agent · Information Extraction

Problem: Manual contract review was slow and inconsistent across large volumes of procurement documents.

Solution: Built an LLM-driven pipeline for pricing-anomaly detection and structured contract-field extraction from raw text.

Impact: Standardized outputs across contract samples and reduced human review effort for recurring document types.

Python LLMs GenAI NLP

Multitool LLM Agent

Agentic LLM System · Tool-Use Orchestration

Problem: Needed a controlled environment to test multi-step reasoning and tool-calling workflows for LLM agents.

Solution: Engineered an API-integrated agent that chains tools, function calls, and reasoning steps via FastAPI.

Impact: Created a reusable testbed for experiments in agent behavior, tool integration, and controllable inference.

Python FastAPI GenAI LangChain

AI Resume Ranking System

NLP Pipeline · ML Classification · Web Service

Problem: Recruiter-style resume screening was manual and inconsistent for different candidate profiles.

Solution: Built an NLP pipeline using TF-IDF features and ML classifiers, exposed via a Flask API for scoring resumes.

Impact: Increased ranking consistency and enabled plug-and-play integration of the model into external workflows.

Python scikit-learn NLP Flask

Work Experiences

2023 – Present

Independent AI/ML Developer

Delivered 15+ ML/LLM systems by building end-to-end Python pipelines integrating LLMs, data processing, and model serving.

  • Improved reproducibility of experiments by containerizing deployments with Docker + CI/CD.
  • Designed function-calling, multi-step reasoning modules aligned with NLU, agent reasoning, and applied-ML research tasks.
  • Led a 3-member GenAI prototyping group, overseeing task assignments, experimentation, and evaluations.
May 2025 – July 2025

AI/ML Intern

BITS Pilani, Hyderabad Campus

Designed and implemented practical machine learning solutions, building and optimizing end-to-end models for real-world decision-making.

January 2025 – May 2025

Undergraduate Research Contributor

Parvathaneni Brahmayya Siddhartha College of Arts & Science

Contributed to an academic research paper on applied AI/ML techniques, participating in ideation, technical write-ups, and literature analysis.

February 2025 – March 2025

AI Intern – TechSaksham (Microsoft & SAP)

Edunet Foundation / AICTE

Selected for a prestigious internship by Microsoft and SAP, focusing on applying AI and software engineering to real-world challenges.

Education

September 2023 - Pursuing

BTech in AI & Machine Learning - PSCMR College of Engineering and Technology

Currently exploring advanced topics in AI, including Large Language Models (LLMs) and Agentic workflows, alongside core full-stack development principles. Maintaining an overall CGPA of 8.2.

September 2021 - March 2023

Intermediate in MPC - Behara Defence Academy And Junior College

Overall CGPA 77.4%

September 2020 – March 2021

Schooling - Sriprakash Vidyaniketan

Overall CGPA - 72%

Certifications & Achievements

JPMorgan Quantitative Research Simulation

Completed a rigorously assessed quantitative-analysis simulation, applying statistical and computational methods to financial datasets.

Hackathon Participant (Devnovate & GDG Build With AI)

Actively participated in national hackathons, delivering functional prototypes focusing on rapid system design, LLM, and GenAI tooling.

Data Analyst (Job Simulation)

Completed a virtual job simulation at Deloitte involving data analysis, dashboard creation with Tableau, and data classification with Excel.

AI Fluency Certification

Verified proficiency in fundamental AI concepts and applications.

Code Vipassana Challenge

Participated in a coding challenge focused on problem-solving and algorithmic thinking.

Google Cloud Training

Completed training modules on Google Cloud Platform services.

Contact

sasisundhar2211@gmail.com

Vijayawada, India