Hi, my name is

Ankit Kumar

AI/ML Engineer & Backend Developer

Highly skilled AI/ML Engineer and Backend Developer with hands-on experience in building and deploying production-grade Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. Proven ability to translate complex data science problems into scalable software solutions.

Resume
Ankit Kumar

About Me

About Me

Hi, I’m Ankit Kumar, an AI/ML Engineer passionate about building intelligent systems powered by Large Language Models, Computer Vision, and Reinforcement Learning. I enjoy turning research ideas into scalable, production-ready AI applications using modern machine learning and software engineering practices.

I’ve worked on AI systems ranging from multimodal and RAG applications to computer vision pipelines and reinforcement learning. During my internship at ISRO, I worked on autonomous lunar landing using Reinforcement Learning, gaining hands-on experience with intelligent decision-making systems.

Technologies I work with:
  • Python, C++ & SQL
  • PyTorch, TensorFlow & OpenCV
  • LLMs, RAG & Multimodal AI
  • Computer Vision & Reinforcement Learning
  • FastAPI, Django & Docker
  • Linux, Git & MLOps

Experience

Indian Institute of Technology, Guwahati
AI/ML Research
Jun 2026 - Present
  • Conducting research on next-generation AI, Machine Learning, and Large Language Model (LLM) architectures with a focus on improving efficiency, reasoning, and scalability.
  • Exploring state-of-the-art Transformer architectures, multimodal models, Mixture of Experts (MoE), diffusion models, and emerging foundation model techniques.
  • Designing and implementing deep learning models using PyTorch and Python for experimentation and evaluation.
Freelance AI/ML Engineer | Consultant
July 2024 – Present
  • Designed and deployed 4+ production-grade Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems for domain-specific applications, achieving a 20% improvement in search/retrieval performance.
  • Built and fine-tuned transformer-based Large Language Models (LLMs), including training a 124M parameter model from scratch.
  • Designed and implemented end-to-end conversational AI solutions that scaled to handle 5,000+ daily user interactions.
  • Reduced harmful output instances by 95% through the implementation of AI safety guardrails and advanced prompt engineering techniques.
Project Intern
May 2024 – July 2024
  • Optimized autonomous Lunar landing simulations using Reinforcement Learning agents, reducing trajectory error margin by 15% over baseline heuristics.
  • Engineered Range Operations data pipelines to process 10,000+ data points per second, enabling real-time fault forecasting with 90% accuracy.
  • Designed a low-level hardware processing layer in Python/C to increase telemetry throughput by 2X and condition GBs of multi-sensor telemetry for RL training loops.
  • Collaborated closely with a team of distinguished Scientists to prototype mission-critical software frameworks.
View the project
Backend Developer Intern
Nov 2022 - Apr 2023
  • Designed and scaled production backend services for a core Chrome Extension and Web ecosystem supporting 10,000+ active users utilizing Django Rest Framework.
  • Accelerated internal search query speeds by 30% through the integration of custom NLP tokenization into PostgreSQL Full-Text Search.
  • Built an asynchronous, automated customer engagement pipeline utilizing Redis and Celery, processing over 5,000 scheduled feedback dispatches daily.
Machine Learning Intern
June 2022 - Oct 2022
  • Developed and cross-validated predictive deep learning frameworks using PyTorch and TensorFlow across 15GB+ unstructured datasets.
  • Designed and benchmarked LSTM-based architectures, improving accuracy by 14% in identifying long-term temporal dependencies within sequential data logs.
Projects

Education

Oct. 2020 – May 2024
Bachelor of Technology in Computer Science and Data Science
Lovely Professional University
GPA: 7.38 out of 10
  • Relevant Coursework: Data Structures, Algorithms, Databases, Computer Systems, Machine Learning, Artificial Intelligence
My academic record
2019 - 2020
High School
Crescent Public School
GPA: 8.0 out of 10
Completed Senior Secondary education with a focus on Science (Physics, Chemistry, and Mathematics), scoring highest in Hindustani Music Vocal (92), along with excellence in Work Experience, Health & Physical Education, and General Studies.

Projects

Tensile Analysis Platform
Python Streamlit SciPy Pandas Statistics
Tensile Analysis Platform
March 2026 – May 2026
  • Designed and deployed a high-performance material characterization dashboard used by a University of Stuttgart research laboratory, automating 90% of complex stress-strain analysis.
  • Built custom mathematical physics solvers, including an optimized Young’s modulus window-search engine using cumulative sum statistics and a strict 0.2% yield strength offset script.
  • Implemented fuzzy-token matching to integrate 100+ unstructured laboratory spreadsheets with raw data, embedding automated statistical analysis (ANOVA, t-tests, IQR outlier detection).
Read Case Study
Modelsmith
Django Deep Learning NLP ML Python
Modelsmith
June 2022 – July 2022
  • Developed a unified model-evaluation web application in Django hosting 10+ distinct machine learning architectures, including custom ResNets and Generative Adversarial Networks (GANs).
  • Authored thorough technical specifications and documentation detailing the underlying linear algebra, backpropagation mechanics, and production deployment parameters.
Visit Site
Multilingual RAG System
LLM Generative AI FAISS Langchain Python
Multilingual RAG System
July 2024
  • Built a multilingual RAG system for PDF documents and books using LangChain and FAISS, enabling fast, context-aware responses across languages.
  • Optimized vector store retrieval and chunking strategies to ensure context accuracy and latency reduction.
Source Code
AquaQuest
Godot Game development
AquaQuest
Nov 2023
  • Developed an educational platformer in Godot for kids (5–6 yrs) teaching the water cycle and groundwater conservation through four interactive levels.
  • Integrated concept scenes, mini-quizzes, and interactive tooltips to reinforce learning through play.
Download

Achievements

UpGrad Hackathon Winner
Created a Django app for Fake News Detection using LSTM with a retraining pipeline and won first prize.
Reinforcement Learning (NPTEL)
Earned NPTEL Certification in Reinforcement Learning from IIT Madras (Jan - Apr 2022).
Python for Data Science (Elite)
Earned Elite NPTEL Certification in Python for Data Science from IIT Madras (Jan - Feb 2022).
Hacktoberfest 2020 Contributor
Contributed to the open-source festival and successfully completed all goals.

Get in Touch

My inbox is always open. Whether you have a question or just want to say hi :)