I build intelligent systems that reason over data, use tools, and turn machine learning research into practical software. My work sits across AI, cybersecurity, data science, and engineering.
Career graph
Education, technology and projects connected through the work.
From data and model development to APIs, reasoning pipelines and deployment, I enjoy working across the layers required to turn an idea into a functioning intelligent product.
LLMs, RAG, agents, computer vision and intelligent automation.
Prediction, anomaly detection, experimentation and data-driven systems.
APIs, backend architecture, deployment and production-minded design.
A selection of machine learning, AI, computer vision and engineering projects built across different problem domains.
Multimedia Systems · Springer Nature
A hybrid machine learning and NLP approach for fake news detection, combining language modelling techniques with a two-tiered detection pipeline and real-time fact-checking considerations.
I’m a builder focused on developing intelligent systems at the intersection of AI, machine learning, software engineering and real-world applications.
I enjoy working across the stack — from understanding data and developing models to designing APIs, reasoning pipelines and the infrastructure required to turn an idea into a functioning system.
AI / ML Systems
Data Science & AI
Intelligent Systems
I’m most interested in projects where machine learning is only one part of the solution and good engineering determines whether the system actually works.
Start with the problem and the constraints rather than immediately choosing a model or framework.
Connect data, models, APIs and infrastructure into something that can actually be used.
Think about evaluation, failure modes, performance and maintainability beyond the initial prototype.
A practical stack spanning machine learning, generative AI, backend development, deployment and embedded systems.
The tools I use to build, experiment and ship.
Models, data pipelines and computer vision systems.
Building applications around modern language models.
Turning models into usable software systems.
Deployment, automation and production workflows.
Connecting intelligent software with physical systems.
BITS Pilani
Data science, AI and machine learning
B.N. Bandodkar College of Science
Physics · Mathematics
CGPA 8.75 / 10
The technologies and ideas I’m spending time understanding more deeply.
Have an interesting problem to solve?
Whether it's an AI system, a research idea, a technical problem, or something that simply needs to be built — I'm always interested in interesting problems.
Based in India · Building at the intersection of AI & engineering.
© 2026 · Atharva Raut