AI & Analytics professional
transitioning into Product Management
With 5+ years building AI and analytics systems, I'm intentionally moving into Product Management. My technical depth in data science, NLP, and analytics platforms is my competitive advantage — I understand technical constraints, can credibly partner with engineers, and make better product decisions grounded in data. Ready to ship products that matter.
M.Tech CSE - Data Science, IIT Jammu · India
Product Impact
Technical Foundation in AI & Analytics
5+ years building production ML/NLP systems and analytics platforms that serve real users at scale. Published research (AAAI 2024), shipped products with 10,000+ daily users, optimized for real constraints (9× speedup, 8× compression). This technical depth is my competitive edge as a PM — I understand engineering possibilities and data-driven evaluation rigor.
ML/NLP Systems · Analytics Platforms · Production Excellence
Building Products That Users Love
Owned products end-to-end: LamiOps analytics platform serving 10K+ users, LamiTracker regulatory intelligence across 200+ sources and 18+ countries. Defined product strategy, aligned stakeholders, measured success with rigorous KPIs, achieved 95% automation of manual work. Shipping products users actually want is what got me excited about product management.
Product-Market Fit · User Obsession · Scaling
PM Ready: The Transition
This career move is intentional. My technical background isn't a limitation — it's a rare advantage. I understand engineering trade-offs, can credibly challenge technical teams, design metrics that matter (not just metrics that look good), and bridge the gap between technical possibility and user value. I'm ready to lead products, not just build systems.
Engineering Credibility · Strategic Thinking · Shipping at Scale
Token by Token
Understanding AI, ML, NLP, LLMs, and Real-World Generative Systems, One Step at a Time
Artificial intelligence doesn't think in moments of magic.
It learns, reasons, and generates outcomes token by token through math, data, and carefully engineered systems.
Token by Token is a technical platform dedicated to understanding modern AI from the inside out. From foundational machine learning concepts to large language models and real-world generative AI systems, this series focuses on how intelligence is built, not just how it appears.
This is not a collection of surface-level tutorials or trend-driven commentary.
Here, we slow things down.
We will explore how Complex ideas like neural networks, optimization, transformers, embeddings, attention, training dynamics, inference pipelines, and deployment trade-offs are broken into clear, intuitive steps. Each article builds on the previous one, helping you form a mental model of how intelligent systems actually work.
The goal is clarity, not intimidation.
There's no hype here. No shortcuts. No "black-box" thinking.
Just careful reasoning, solid engineering, and honest explanations,
built one concept, one decision, one token at a time.
If you want to move beyond using AI tools and start understanding the
systems beneath them,
you're in the right place.
Welcome to Token by Token.
Let's Collaborate
Whether you're looking for an AI Product Manager to own your GenAI roadmap, a consultant to translate business problems into scalable AI systems, or a thought partner on your AI strategy — I'd love to connect.
Open to AI PM roles, consulting engagements, advisory opportunities, and mentoring conversations.