Hi, I'm Nageeta (Nigeeta) Kumari
AI/ML Engineer & Software Engineer with expertise in building intelligent systems using machine learning, natural language processing, and modern software engineering practices. I hold an MVA from École Normale Supérieure Paris-Saclay and have worked on applied AI research and engineering at Quicksort and Datadog, building agentic LLM pipelines, evaluation frameworks, and scalable data systems. I'm always open to new, challenging opportunities — feel free to get in touch to connect, share, or discuss ideas.
Work Experience
Quicksort – Applied AI Engineer Jan 2026 – Present
❗ Problem: Extracting structured information from complex, unstructured financial documents at scale is slow and error-prone.
🧩 Strategy: Designed agentic LLM pipelines paired with robust evaluation frameworks to measure and improve extraction quality.
✅ Solution: Built and deployed agentic data extraction pipelines using Google ADK, Docling, and OpenSearch; collaborated with DevOps to set up Kubernetes monitoring with Grafana and OpenSearch.
🛠️ Tools: Google ADK, Docling, OpenSearch, Kubernetes, Grafana, Python, Evaluation Frameworks
📚 What I Learned: Building production-grade agentic pipelines, evaluation-driven development, and cross-team collaboration on ML infra.
Datadog – AI/ML Research Intern Apr 2025 – Oct 2025
❗ Problem: Distributed microservices produce complex trace data, making root cause analysis challenging and costly.
🧩 Strategy: Formulated the problem as a probabilistic modeling challenge, explored unbiased data sampling, and compared evaluation methods.
✅ Solution: Designed models for root cause analysis, implemented unbiased data pipelines, and built an evaluation framework achieving 95% recall & 77% precision.
🛠️ Tools: AWS, Trino-SQL, Docker, Mortor, NBT, Unsupervised Learning, Causal AI
📚 What I Learned: Applied AI research in production-scale systems, theory-engineering balance, multicultural teamwork.
INRAE – Research Intern Feb 2024 – Jul 2024
❗ Problem: INCA2 and INCA3 surveys had inconsistent nomenclature, blocking unified classification.
🧩 Strategy: Applied ontology mapping & semantic web tech to harmonize datasets.
✅ Solution: Built GPT-3.5 pipeline to map INCA2 into FoodEx2 for interoperability.
🛠️ Tools: GPT-3.5, Python, Ontology Dev, Semantic Web
📚 What I Learned: Data harmonization, semantic tech, handling real-world noisy data.
SoundM / DLLC – Software Engineer Aug 2022 – Aug 2023
❗ Problem: Need for secure, scalable communication platform.
🧩 Strategy: Designed secure back-end systems integrated with front-end features.
✅ Solution: Built chat systems, authentication, profile APIs, and deployed on AWS.
🛠️ Tools: React.js, Node.js, FastAPI, AWS
📚 What I Learned: Real-time systems, startup environment, cross-functional teamwork.
Freelancer – Fiverr 2020 – 2022
Fiverr Profile: fiverr.com/nageeta_w
❗ Problem: Clients needed secure web apps with fast delivery & low cost.
🧩 Strategy: Defined scope, built clean UI, deployed scalable solutions.
✅ Solution: Delivered full-stack projects (auth, APIs, dashboards) with high satisfaction.
🛠️ Tools: React, Node, FastAPI, PostgreSQL, MongoDB, AWS, Docker
📚 What I Learned: End-to-end project delivery, client management, solo development.
Education
École Normale Supérieure Paris-Saclay – MVA Sep 2024 – Sep 2025
Grade: 16/20
Selective AI Master's in computer vision, learning, and mathematics.
Courses:
- Reinforcement Learning
- Probabilistic Graphical Models
- Advanced Deep Learning
- Large Language Models
- Geometric Data Analysis
- Machine Intelligence of Images
Université Paris-Saclay – Master in Data Science Aug 2023 – Aug 2024
Grade: 15.7/20
Courses:
- Advanced Databases, Distributed Systems
- Deep Learning, NLP, ML Algorithms
- Information Theory, Probability
Sukkur IBA University – BS in CS Aug 2018 – Aug 2022
Grade: 3.68 / 4
🏅 Silver Medalist
Courses: Software Engineering, Object Oriented Programming, Web Enterprise Development, Database Design, Data Structures, Advanced Algorithms, Business Communication, Cloud and Parallel Computing, Robotics, Cyber Security, IoT
Projects
Modeling for MNAR Data (not-MIWAE)
Re-implemented not-MIWAE generative model and benchmarked it on UCI & stock datasets.
Tools: PyTorch, Python
Composed Image Retrieval
Adapted CoVR-BLIP-2 for CIRR dataset and improved Recall@1 with attention pooling.
Tools: Vision-Language Models, PyTorch
Patent Match Challenge
Used sentence-transformers and fine-tuned BERT models for patent citation matching.
Tools: NLP, Transformers
Compositional Understanding in VLMs
Evaluated VLMs on ARO benchmark, showing improved performance of Qwen2.5 over CLIP/BLIP.
Tools: Vision-Language Models, PyTorch
RelevAI-Reviewer (Benchmark System)
Relevance ranking for survey papers vs CFP prompts using ML baselines & fine-tuned transformers.
Tools: Transformers, Python
Scrimish (Android Game)
Android implementation of Scrimish card game with game logic and UI design.
Tools: Android Studio, Java
SIBA Stack Overflow (Q&A Web App)
Student/teacher Q&A platform with React.js, Node.js, MySQL.
Tools: React.js, Node.js, MySQL
Gender Detection Using Eye
CNN model predicting gender from eye images with preprocessing and training pipeline.
Tools: CNN, Python, TensorFlow
Publications
RelevAI-Reviewer: A Benchmark on AI Reviewers for Survey Paper Relevance
Authors: Paulo Henrique Couto, Quang Phuoc Ho, Nageeta Kumari, Benedictus Kent Rachmat, Thanh Gia Hieu Khuong, Ihsan Ullah, Lisheng Sun-Hosoya
Conference: Conférence sur l'Apprentissage Automatique (CAp) 2024, Lille, France
Abstract: Recent advancements in AI, particularly Large Language Models (LLMs), offer promise for automating scientific paper review. This paper proposes RelevAI-Reviewer, an automatic system that conceptualizes survey paper review as a classification problem, aimed at assessing paper relevance to specified prompts. We introduce a novel dataset of 25,164 instances and explore various baseline approaches including traditional ML classifiers like SVM and advanced language models such as BERT.
Awards & Honors
Silver Medal Apr 2023
Issued by: Sukkur IBA University
Silver Medalist for achieving the second-highest position based on Bachelor's CGPA in Batch 2018.
Robotics Competition May 2022
Issued by: CRAIB Lab, Sukkur IBA University
Participated in a robotics competition where students assembled and programmed robots for specific tasks. Worked with a team on a spider robot using 3D printed parts, programmed to access hidden areas that are hard for larger robots to reach.
Merit Scholarship 2019 Dec 2019
Issued by: Sukkur IBA University
Institutional merit-based scholarship awarded to the Top 3 students of the department based on Fall semester GPA for the entire academic year.
Mathematics Olympiad Winner Aug 2018
Issued by: Sukkur IBA University
Won the Mathematics Olympiad competition hosted by Sukkur IBA University with its sub-campuses for foundation semester Batch 2018.
Contact Me
I'd love to hear from you! Feel free to reach out via email or connect with me on LinkedIn.
Email: nageetaw@gmail.com
LinkedIn: linkedin.com/in/nageeta124
GitHub: github.com/nageetaw