About Me
Rishabh Indoria – ML / AI Engineer
Greetings! I’m an ML/AI Engineer focused on building end-to-end intelligent systems, from data ingestion and modeling to deployment and real-world integration. My work spans agentic AI, computer vision, and applied machine learning, with an emphasis on robustness, scalability, and practical impact.
Across my projects, I’ve built systems involving knowledge graphs with reasoning, Vision Transformers under resource constraints, and predictive models trained on large, noisy datasets, bridging the gap between ML research concepts and production-ready implementations.
Core Expertise
Machine Learning & AI
- Deep Learning, Classical ML
- NLP, Knowledge Graphs, Retrieval-Augmented Systems
- Computer Vision, Vision Transformers
Systems & Engineering
- Python, PyTorch, TensorFlow
- FastAPI, ML model serving
- End-to-end ML pipelines & inference systems
Data & Modeling
- Feature engineering (numeric, categorical, text)
- Large-scale dataset handling
- Model evaluation & optimization
Innovation and Problem-Solving
I enjoy tackling complex, ill-defined problems and turning them into clean, reproducible, and deployable solutions. Whether it’s optimizing models for latency, designing fault-tolerant pipelines, or simplifying complex ML workflows, I prioritize clarity, reliability, and impact.
Continuous Learning
The ML landscape evolves quickly, and I continuously explore new architectures, tools, and ideas, particularly in agentic systems, transformers, and scalable ML engineering, to improve both model performance and system design.
Collaboration and Communication
I value clear communication and structured collaboration. Building strong AI systems often requires aligning ML, engineering, and product thinking. I enjoy working at that intersection.
Get in Touch
Interested in agentic AI systems, applied ML, or production-grade AI pipelines? I’m always open to conversations around meaningful ML work and real-world AI deployment.
Let’s build intelligent systems that make an impact!