Fine-Tuning Open-Weights Models with QLoRA & Unsloth
A practical hands-on guide to parameter-efficient fine-tuning (PEFT): 4-bit quantization, Low-Rank Adaptation (LoRA), Memory footprint management, and 2x faster training with Unsloth.
Read article
SYSTEM STATUS: ALL AI & ML MODELS OPERATIONAL
⚡ High-Performance Systems
⚡ Executive AI Engineering
🔒 Production Ready
EXECUTIVE AI & ML ARCHITECT Rushikesh Mohalkar
I build
AI/ML Systems
Deep Learning Models
Computer Vision
RL Autonomous Agents
Generative AI
AI/ML Systems
Building RAG pipelines, autonomous multi-agent systems, and deep-learning architectures from scratch — no black boxes. 20+ production-grade projects shipped across LLMs, computer vision, and reinforcement learning.
19+
ML Projects
25+
Articles Written
3
Built From Scratch
2
Production-Grade Systems
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.
Together, they're the building blocks of tomorrow's intelligent world.
— Rushikesh Mohalkar
About Me
The AI Odyssey — from curiosity to craft
✦ the story
Turning math, code & GPUs into production AI systems.
I'm an AI/ML Engineer specializing in Large Language Models, Agentic Architectures, Deep Learning, and Production ML Pipelines. I build scalable RAG architectures, fine-tune open-weights models (Llama 3, Qwen, Mistral), and construct autonomous AI agents that plan, critique, and execute tool calls with high reliability.
From low-level model optimization to real-time evaluation harnesses and production deployment, I focus on turning complex machine learning research into resilient, real-world software applications.
19+
Projects shipped
25
Articles written
🎯 currently exploring
Agentic AI & MCP
LLM Fine-Tuning
Test-Time Compute
Production RAG & Eval
Open to AI/ML & GenAI roles
📍 Bengaluru, India · Remote & Global Ready
☕ fun fact
Once spent 48 hours straight debugging a loss spike — only to find a index alignment error. AI engineering teaches math, code, and relentless perseverance.
🧠 technical arsenal
Python
PyTorch
LLMs & Transformers
Agentic Workflows
RAG Architecture
Vector DBs & FAISS
LangChain / LlamaIndex
Fine-Tuning (LoRA/QLoRA)
Reinforcement Learning
Computer Vision
Deep Learning
Scikit-learn
NumPy & Pandas
FastAPI & Docker
Git & MLOps
Featured Work
Projects that learn & adapt
A selection of AI/ML systems I've designed, trained, and shipped.
Multi-Agent Orchestration: Designing Reliable Autonomous Workflow Systems
A comprehensive technical architectural guide to building production multi-agent systems: task decomposition, agent delegation, state isolation, handoff contracts, and failure recovery.
Read articleProduction RAG Engineering: Hybrid Search, Reranking & Evaluation
An end-to-end technical deep dive into moving beyond naive vector RAG: dense+sparse hybrid search, cross-encoder reranking, chunking strategies, and automated evaluation metrics.
Read articleTest-Time Compute & Inference Scaling for Reasoning Models
A deep technical analysis of the shift from pre-training compute scaling to inference-time scaling: Monte Carlo Tree Search (MCTS), Process Reward Models (PRMs), and self-correction loops.
Read articleAgent Harnesses: The Engineering System Around Reliable AI Agents
A technical guide to building agent harnesses: the runtime, state, tools, policies, evaluation, and observability that turn an LLM loop into a dependable system.
Read articleDeploying Models in Production: A Technical Guide from Artifact to SLO
A practical deep dive into production model deployment: packaging, serving, scaling, rollout strategies, observability, and the failure modes that matter after training.
Read article
Interactive Resource
The complete AI & ML mind map
A single visual map of the entire machine-learning landscape — from supervised learning to transformers and diffusion — with the core math on every node and click-through diagrams of how the flagship algorithms actually work.
Writing
Notes on AI & intelligence
Deep dives on architectures, research, and the ideas shaping modern AI.
Fine-Tuning Open-Weights Models with QLoRA & Unsloth
A practical hands-on guide to parameter-efficient fine-tuning (PEFT): 4-bit quantization, Low-Rank Adaptation (LoRA), Memory footprint management, and 2x faster training with Unsloth.
Read articleMulti-Agent Orchestration: Designing Reliable Autonomous Workflow Systems
A comprehensive technical architectural guide to building production multi-agent systems: task decomposition, agent delegation, state isolation, handoff contracts, and failure recovery.
Read articleProduction RAG Engineering: Hybrid Search, Reranking & Evaluation
An end-to-end technical deep dive into moving beyond naive vector RAG: dense+sparse hybrid search, cross-encoder reranking, chunking strategies, and automated evaluation metrics.
Read articleTest-Time Compute & Inference Scaling for Reasoning Models
A deep technical analysis of the shift from pre-training compute scaling to inference-time scaling: Monte Carlo Tree Search (MCTS), Process Reward Models (PRMs), and self-correction loops.
Read articleAgent Harnesses: The Engineering System Around Reliable AI Agents
A technical guide to building agent harnesses: the runtime, state, tools, policies, evaluation, and observability that turn an LLM loop into a dependable system.
Read articleDeploying Models in Production: A Technical Guide from Artifact to SLO
A practical deep dive into production model deployment: packaging, serving, scaling, rollout strategies, observability, and the failure modes that matter after training.
Read article
Journey
Résumé & Experience
My professional path, education, and the skills I'm building on.
💼 Experience
July 2024 — Present
QA Engineer
CognizantEnsuring software quality through testing, automation, and process improvements while deepening my AI/ML foundations on the side.
Ongoing
AI/ML Engineer
Independent & Project-BasedBuilding AI/ML systems with a focus on deep learning, reinforcement learning, and production-grade intelligent systems.
🎓 Education
2019 — 2023
BE in Electronics & Telecommunication
AISSMS IOIT, Pune • SPPUFoundation in electronics, communication systems, and software engineering.
Contact
Let's build something intelligent
Have a project, a question, or just want to talk AI? I'd love to hear from you.
Reach out directly
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