Ayushi Jain

Hi, I’m Ayushi Jain, a Software Engineer at Microsoft with a curious mind and a passion for building highly scalable, intelligent systems that learn, reason, and collaborate adhering to principles of high reliability and security.

🔗 Connect With Me

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At Azure, my work spans across A2A and MCP protocol integrations, large-scale cloud automation across 20+ regions, and secure B2B authentication flows. Along the way, I continue to strengthen my core software engineering skills in distributed systems, backend architecture, and DevOps.

I began my journey at Microsoft as an intern, where I optimized machine learning libraries on single machine, and built PoCs for distributed ML using PySpark and Databricks, and since then, my curiosity for scalable and intelligent systems has only grown stronger.

Before joining Microsoft, I earned my B.Tech. in Computer Science Engineering from IIIT Delhi (CGPA: 8.34), where I developed a deep interest in distributed systems, machine learning, and deep learning. I continue to explore these areas through courses like Stanford’s XCS234 (Reinforcement Learning) and XCS236 (Deep Generative Models), Azure certifications, Kaggle competitions and independent exploration.

Outside of work, I enjoy reading fiction and non-fiction, and experimenting with side projects that combine AI, systems design, and creativity.
This blog is my space to document what I learn and build, not just as a record of progress but as a way to make AI and engineering more approachable for others.

This site is powered by curiosity, continuous learning, and the belief that knowledge grows best when shared.

🎯 Professional Milestones

  • SWE @ Microsoft (L59 → L60) — 2023 - Present
    Working in Azure Specialized org building Agentic AI systems

  • Microsoft Azure Certifications — 2024
  • Stanford University (Advanced AI Courses) — Stanford Online, 2024
    • CS234: Reinforcement Learning (Winter 2024) — Covered foundational and advanced RL techniques including policy gradients, Q-learning, and bandit algorithms, with a focus on sequential decision-making under uncertainty.
    • CS236: Deep Generative Models (Summer 2024) — Explored generative modeling techniques such as VAEs, GANs, Normalizing Flows, and Diffusion Models, emphasizing both theory and implementation.
  • SWE Intern @Microsoft — Microsoft, May 2022 - July 2022
    • Optimization of Microsoft’s internal Machine learning library: written using deep learning libraries and algorithms in python based on paper written by MSFT Research leading to reduction in memory usage by 75% on 100+ GB datasets using time profiling, vectorization and reduction in logging.
    • Built a distributed ML PoC using PySpark and Databricks demonstrating scalable pre-processing and training on large-scale datasets.
    • Secured a return offer from Microsoft 😊
  • Dean’s Award for Excellence in Teaching Assistantship — IIIT Delhi, 2022
    • Received appreciation for mentoring 400+ students of junior batches in IIIT Delhi in DSA
    • As a part of TAship, prepared assignments, took tutorials and office hours for students.
  • Machine Learning Engineer — Wunderman Thompson Salmon, May 2021 - July 2021
    • Implemented a recommendation system to predict customers’ next baskets based on the paper using PyTorch.
  • Research Publication — ACM Hypertext Conference, 2022

🛠️ Technical Skills

Languages & Frameworks
Python • C# • .NET • JavaScript • Java • KQL • C++ • ReactJS

AI & Machine Learning
PyTorch • TensorFlow • Scikit-learn • LangChain • Semantic Kernel • Azure AI Foundry • OpenAI APIs • RAG Systems • Agent Architectures • Reinforcement Learning

Cloud & Infrastructure
Azure (Cosmos DB, Azure Functions, App Services, Authentication, Azure ML) • Docker • Kubernetes • CI/CD (GitHub Actions, Azure DevOps)

Tools & Platforms
Git • VS Code • Jupyter •

🎓 Academic Background

IIIT Delhi | B.Tech. in Computer Science Engineering | 2019 - 2023
Courses: Machine learning, Natural Language Processing, Collaborative Filtering, Distributed Systems, Theory of Computation, Advanced Data Structures and Algorithms, Computer Networks, Operating Systems
CGPA: 8.34/10

Class 12 (CBSE) | DAV Public School, Shreshtha Vihar, Delhi | 2019
Subjects: Physics, Chemistry, Mathematics, English, Physical Education
Percentage: 95.4%

NTSE Scholar (National Talent Scholar Examination - Class 10th) | 2017
About the exam: It is conducted by the National Council of Educational Research and Training (NCERT) with the Government of India. The exam is taken in two stages - at state and national level. There are three papers at every stage: MAT (Mental Aptitude Test), English Language Test, SAT (Scholastic Aptitude Test) - covering topics ranging from logical reasoning, physical and social sciences.
Among top 750 students in India in class 10th to clear the exam.

Class 10 (CBSE) | Cambridge School, Indirapuram | 2014
CGPA: 10/10

Test Scores

JEE Advanced | Joint Engineering Entrance (Advanced) Exam | 2019
Top 0.3 percentile amongst 100k applicants
AIR: 11404

JEE Mains | Joint Engineering Entrance Exam | 2019
Top 0.27 percentile amongst a million applicants
AIR: 3366

📚 Books I Have Recently Read

  • The Silent Patient, Alex Michaelides
  • All The Light We Cannot See, Anthony Doerr
  • The Story Of My Life, Helen Keller
  • More Days At Morisaki Bookshop, Satoshi Yagasawa
  • Days At The Morisaki Bookshop, Satoshi Yagasawa
  • The Murder of Roger Ackroyd, Agatha Christie
  • And Then There Were None, Agatha Christie
  • How To Kill Your Family, Bella Mackie

Thanks for stopping by — and if you’re building something cool in AI, I’d love to hear from you! Please feel free to reach out at atallakshaya@gmail.com
This is my personal website, and all thoughts posted here are only mine and not linked to the workplace I am at.