Adil R. Mallick
Software Engineer & Cloud Infrastructure Developer
Computer Science @ Michigan State University | Specializing in Full-Stack Development & Cloud Solutions
Education
Michigan State University
B.S. in Computer Science, Minor in Business
Expected Graduation: May 2027 | Lansing, MI
Coursework: Data Structures & Algorithms, Modern C++ Programming, Discrete Mathematics, Multivariable Calculus, Computer Systems & Architecture, Linear Algebra & Matrix Computations
Experience
DTE Energy
Cloud and Infrastructure Intern
June 2025 – Present
- Designed and implemented a chatbot for Microsoft Teams using Terraform, integrating APIs (e.g., ServiceNow) to retrieve and present data for 500+ enterprise users
- Utilized Microsoft Azure to provision resource groups and deploy APIs, ensuring scalable and reliable backend infrastructure reducing load times by 27%
- Collaborated in Agile sprints to develop backend systems supporting cloud and DevOps workflows in a fast-paced enterprise environment
- Integrated Power Automate front-end, increasing user efficiency by 50%
Alchemy Software
Software Engineer
Sep. 2024 – May 2025
- Collaborated with a cross-functional team to design and implement a comprehensive task management application using React, Next.js, and Electron.js
- Developed Python automation scripts for email list management utilizing smtplib and pandas to streamline data processing by 33%
- Developed a serverless architecture on Cloudflare, integrating API gateway, CloudFormation, and CloudWatch to streamline backend processes, achieving a 33% reduction in loading times
- Built a responsive site for Half-Full Task Manager, improving memory efficiency by 46%
Huda Clinic
Software Engineering Intern
May 2024 – Aug. 2024
- Refactored and streamlined patient onboarding processes by 40% through the integration of Athenahealth APIs, enabling automated data intake and reducing manual entry across healthcare workflows
- Designed and implemented a fully responsive, mobile-first UI using modern frameworks, significantly improving performance by 28% and increasing accessibility across multiple platforms
Featured Projects
ZenTube
Next.js, React, Node.js, Tailwind CSS, YouTube Data API v3
Engineered dynamic routing system using Next.js file-based architecture and [param] folders, enabling SEO-optimized URLs across 3+ core pages and improving user navigation by 30%
Designed 3 custom serverless API endpoints to efficiently proxy YouTube Data API calls, reducing frontend load time by 40% through asynchronous data fetching
View on GitHub →Movie Recommender System
Python, Scikit-learn, Pandas, NumPy, Streamlit
Built a hybrid recommendation engine combining collaborative filtering (NMF) and content-based filtering (TF-IDF + cosine similarity), achieving 23% higher accuracy over baseline models
Implemented an end-to-end ranking pipeline (recall, first-stage, final scoring) with sparse matrix optimizations, reducing query latency by 35% and enabling real-time recommendations via an interactive Streamlit dashboard
View on GitHub →Technical Skills
Programming Languages
Frameworks & Libraries
Tools & Platforms
Certifications
Let's Connect
Feel free to reach out for collaborations or opportunities!