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  • Microsoft
  • Hyderabad, INDIA
  • 10:12 (UTC +05:30)

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Achievement: Pull Sharkx2Achievement: YOLOAchievement: Quickdraw

Achievements

Achievement: Pull Sharkx2Achievement: YOLOAchievement: Quickdraw

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arshitas/README.md

Namaste, I am Arshita Shukla 👋

Embedded Systems | Hardware-Software Co-design | Platform Management | System on Chip | Baremetal Programming | Cloud | Open-source | Gen AI

  • 👩‍💻 Firmware Engineer at Microsoft, building firmware and system software for cloud-scale hardware platforms.
  • 🤖 AI systems enthusiast, fascinated by AI accelerators, cloud infrastructure, distributed training, and inference systems. I enjoy following the latest research and industry developments shaping the future of AI.
  • 📚 Outside of work, I spend a lot of my time reading AI research papers, systems blogs and technical deep dives on large-scale AI training and inference
  • 🎓 Completed my undergrad in Electronics & Communication Engineering from NIT Surat, Gujarat (2022)
  • 🛰️ My undergrad thesis focused on application of satellite communication and is also published!(IEEE Xplore link)
  • 🇫🇷 Former Research Intern at Inria, France
  • 🏸 When I’m not debating hardware vs software performance, you’ll find me geeking out over sports (especially badminton)

GitHub Stats

My Awesome Stats arshitas's Streak

Tools I use

Badges

arshita-shukla's Credly stats card

An image of @arshitas's Holopin badges, which is a link to view their full Holopin profile

Connect

  1. Mail: arshitashukla.27@gmail.com
  2. Linkedin: https://www.linkedin.com/in/arshita-shukla-b656821ab/
  3. Discord: arshita_10188
  4. Zulip: https://rust-lang.zulipchat.com/#user/895436

Pinned Loading

  1. accelerator_simulator accelerator_simulator Public

    Lightweight Accelerator Simulator

    C++

  2. linux-chatbot linux-chatbot Public

    Linux Documentation RAG Chatbot

    Python

  3. model_inference model_inference Public

    End to End ML Inference and deployment

    Python

  4. metric_calculator metric_calculator Public

    Pyspark pipeline to calculate performance metrics of common microservices

    Python