Chandan Cj Jain

About Chandan Cj Jain

Hello! I\'m CJ, a software engineer at Meta!My career began in IOS development. I had the privilege of interning at a tech agency, where I designed and implemented features utilizing Swift\'s RealityKit. I continued pursuing IOS development full time for 2 years, owning entire applications both on existing codebases and creating them from scratch.After several years of focusing on mobile development, I made the transition to a non-iOS role at AWS, which has proven to be immensely helpful in expanding knowledge base. It gave me the chance to work with nearly all the services available on native AWS to put together our very own Network Firewall ServiceAt my time at AWS, I learned an immense amount of infrastructure engineering by working on distributed systems. Learning the networking and cybersecurity became a byproduct of working in the network firewall industry, where domain expertise was crucial for serving our customers. Being a very process driven organization, this is where I sharpened my process driven mindset for scaling and driving solutions.At Meta, I was offered an amazing opportunity to work in the cutting edge MTIA team, where we build GPUs in house tailored to the many different applications of ML and AI at Meta. This is where I was lucky enough to work with top industry talent in ML/GPU technology and soak up all the knowledge I could!

Experience

1. Software Engineer

   Meta

   Jul 2024 — Present · New York, NY, US

   MTIA (1 year)- Meta Training and Inference Accelerator - Meta\'s own GPU made from scratch tailored to our ML and AI workflows. Our domain is in the software stack sitting underneath PyTorch and on top of chip firmware, we specialize in model lowering w/ graph and compiler optimizations, smooth runtime integration for fast inference and training jobs, and hardware specific kernel writing (in a variety of styles, C manual kernels, Triton kernels, and Inductor). All of this leads to 2-3x perf/cost of running our chips over our competitors creating scalable savings, allowing for new innovation in the AI chip spaceWearables (current)- With the release of Ray Ban Display glasses, there is a whole new element of interaction with technology. We now present EMG controlled devices allowing for a very seamless and non disruptive way to interact with technology. This input modality brings a unique set of problems not solved before and I specifically work on the handwriting aspect.I spent 1 year on MTIA before making the exciting switch to Meta Neural Band for the Meta Rayban Glasses. Going from maximum compute in large data-centers to a heavily resource constrained device is all about scaling down our models and writing lightweight performant code. It\'s been very cool to work on model optimizations for very large models and very small ones, with lots of overlaps in concepts with greatly differing applications. Excited to see all the future use cases of EMG tech (and help make it happen)!

Education

• UC Irvine

  Computer Science and Engineering, B.S., Donald Bren School of Information and Computer Sciences AND Henry Samueli School of Engineering

• John P. Stevens High School

  High School Diploma