Hi, I'm Rushikesh Mohalkar
I'm a
Passionate and curious AI/ML enthusiast transitioning into the world of software and intelligent systems. Exploring generative AI, deep learning, and reinforcement learning to make systems smarter and impactful.
The future of AI isn't about replacing humans — it's about amplifying human intelligence. Machine Learning teaches patterns, Deep Learning reveals hidden insights, and Reinforcement Learning shows us how to adapt and improve.
Together, they're the building blocks of tomorrow’s intelligent world.
— Rushikesh Mohalkar
About Me
Get to know me better
The AI Odyssey: From Curiosity to Passion
I'm an AI/ML engineer in the making who loves turning math, code, and GPUs into real systems. Most of my work lives at the intersection of deep learning, reinforcement learning, and generative models.
I’ve built and shipped models for recommendation (RBMs), time‑series forecasting (RNN/LSTM), and medical imaging (CNN‑based diagnostic models), along with agents that learn to drive in simulators using PPO.
Recently, I’ve been exploring LLM tooling—from retrieval‑augmented generation and evaluation pipelines to small autonomous agents that can plan, critique themselves, and iterate toward a goal.
Long‑term, my goal is to work on robust, production‑grade AI systems that are explainable, reliable, and actually useful for people— especially in domains like healthcare, finance, and tools for engineers.
What I’m focused on now
I’m actively exploring practical reinforcement learning for real-world systems, scalable model deployment, retrieval-augmented generation, and evaluation frameworks for LLM applications. On weekends, I tinker with small agents that can plan, critique their own output, and iterate toward a goal.
I care deeply about writing maintainable code, clean interfaces, and building tools that other people enjoy using. Clear naming, small abstractions, and fast feedback loops are my favorite engineering superpowers.
Beyond the code
- Mentoring peers who are transitioning into AI/ML from adjacent fields.
- Reading research to bridge the gap between papers and production.
- Designing delightful user experiences for technical tools and dashboards.
Fun fact: I once spent 48 hours straight debugging a neural network, only to realize I had a typo in my loss function. The lesson? AI teaches you patience, persistence, and the importance of coffee! ☕
Technical Arsenal
Featured Projects
Explore my latest AI/ML work
Blog Posts
Thoughts and insights on AI/ML
Get In Touch
Let's work together on your next AI project
Let's Connect
I'm always interested in new opportunities and collaborations. Whether you have a project in mind or just want to chat about AI/ML, feel free to reach out!
Resume & Experience
My professional journey, skills, and achievements in the field of AI and Machine Learning.
Current Resume
Experienced AI/ML Engineer with expertise in deep learning, computer vision, and natural language processing. Passionate about developing innovative solutions and pushing the boundaries of artificial intelligence.
Experience
QA Engineer
Cognizant • July 2024 - Present
Ensuring software quality through testing, automation, and process improvements.
Aspiring AI Engineer
Future Role
Preparing to transition into Artificial Intelligence engineering, focusing on machine learning and deep learning.
Education
MSc in Computer Science (Future)
AI University • Expected 2026 - 2028
Planned specialization in Artificial Intelligence and Machine Learning.
BE in Electronics & Telecommunication (ENTC)
AISSMS IOIT, Pune • SPPU University • 2019 - 2023
Foundation in electronics, communication systems, and software engineering.
Skills
