Hello! I’m an engineer by choice and heart and I love solving problems. I am not married to any school of engineering and love learning about varying technologies. I am also an active learner of biology and physics.

I have a background in Electronics and Communication Engineering. I haven’t pursued electronics in a while now in pursuit of ML but in past life have actively built autonomous robots. I feel equipped now to merge both domains of engineering to solve “big” problems.

Professionally, I am an AI Engineer at Weights and Biases (by CoreWeave). I lead our open source integration efforts primarily. These integrations make it easy for you ML practitioners to get an MLOps stack. Currently I am specializing in building LLM applications and doing model evaluations. But over the span of 5 years at W&B, I have worn multiple hats – like leading our Kaggle initiatives, building our most popular courses, and a ton loads of reports that SEO really well. Overall, the technical efforts have contributed to a successful merger of W&B with CoreWeave and I have big plans.

I am also a Google Developer Expert in Machine Learning and a Kaggle Master (notebook).

When I’m not coding, I enjoy watching anime (Naruto is my all-time favorite!) and sharing knowledge through technical articles. I have started with 3D printing as well. Stay tuned!

Know more about me from here. My external articles and other work are listed here. A detailed account of my projects can be found here.

News

  • New work on RAG evaluation: RAG Techniques: From Naive to Advanced - a comprehensive guide to Retrieval Augmented Generation techniques.
  • New work: LLM Evaluation Framework with systematic evaluation approaches using W&B Sweeps.
  • New work: Building MLOps pipelines for Keras integration with comprehensive monitoring and tracking capabilities.
  • Gave a course on RAG++: From POC to Production covering practical implementation strategies. Find the materials here.
  • Open-sourced SwAV-TF, a TensorFlow implementation of self-supervised visual representation learning.

To know more about my projects, please refer to my GitHub profile.

Apart from the work here, I try to contribute to other platforms in the form of writing and open-source contributions. Please refer here for more details.