About Me
I appreciate your interest in learning more about me. While this space offers a glimpse, I believe in the value of genuine professional connections. I welcome you to reach out via my social channels, where we can engage in meaningful discussions about our experiences, insights, and potentially explore collaborative opportunities in our field.
I currently work as a Senior Solutions Architect at NVIDIA, partnering with enterprises, public-sector institutions, and higher education and research organisations on the design and deployment of accelerated AI solutions. My focus is on large-scale Generative AI, AI agents, large language models, LLM post-training, model training and inference, and the infrastructure and platform choices needed to operationalise these workloads in AI factories.
Across 7+ years in data science, machine learning, developer advocacy, and solutions architecture, the core thing I have learnt is to solve real problems with systems that can survive contact with messy data, changing requirements, and real users. I like building fast feedback loops: get the first useful version running, measure what matters, then keep tightening the solution.
My current technical focus is Generative AI beyond the demo layer: multi-agent systems, tool-using and reasoning workflows, LLM post-training, inference, evaluation, deployment, and the architecture required to operate these systems reliably at scale. I take a practical, full-stack approach that helps teams move from AI concepts to real systems they can build, optimize, deploy, and operate. I also continue to work across large-scale data processing, traditional machine learning, deep learning, and accelerated computing.
I regularly develop and deliver keynote sessions and hands-on technical workshops at customer and partner events, translating complex AI systems into architectures, implementation patterns, and practical lessons that technical audiences can apply to their own workloads.
Before moving into solutions architecture, I was a GPU Developer Advocate with NVIDIA’s OpenHackathons Group. I helped developers, researchers, and industry teams move AI and scientific workloads closer to production-grade GPU acceleration through hackathon mentorship, technical enablement, and guidance on performance, deployment, and architecture choices.
Before NVIDIA, I was a Manager & Lead Data Scientist at Shiprocket, where I built data-heavy and scalable ML pipelines across Tabular ML, NLP, logistics intelligence, fraud detection, address intelligence, and time-series forecasting.
Before that, I had a short stint at Whitehat Jr., an EdTech company, where I worked on clustering, segmentation, data crunching, and dashboards used by CxO teams. I began and evolved into data at EXL, where I transformed slow, monolithic projects built in proprietary tools into faster, modular, interpretable, and user-friendly solutions.
Some of my key projects are listed here. I also undertake courses and certifications to keep myself up to date with this rapidly evolving domain.
Education
National Institute of Technology (NIT), Kurukshetra
Bachelor of Technology (B.Tech) in Electrical and Electronics Engineering
Specialisation: Data Science and Computer Application
CGPA: 8.5/10
Years: 2015-2019
St. Dominic’s School, Mathura
| Examination | Class | Score |
|---|---|---|
| All India Senior Secondary Examination | XII | 94.2% |
| All India Secondary School Examination | X | CGPA 10/10 |
I have no defined interests 🙈 and take up and try different things. Trying to keep a memoir here. Besides that, I am a watch aficionado and 🍺 buff.
I also try to maintain some lists for my:
On most platforms, you’ll see me going by the alias boi-doingthings.