ANUJ WADI

Software Engineer | AI & Machine Learning | Robotics

Who am I?

Anuj Wadi is a Software Engineer working across AI, Machine Learning, and Robotics, with an MS in Robotics and Autonomous Systems (AI) from Arizona State University. He builds intelligent systems that combine agentic AI, machine learning, and autonomous systems to solve real-world problems โ€” from a production AI-assisted Blood Bank Management System deployed across 3 hospitals to a multimodal conversational AI runtime with sub-200ms end-to-end latency. His work spans agentic workflows and RAG pipelines, transformer fine-tuning, and cloud-native backends, bridging research with practical, production-grade deployment across healthcare, finance, and robotics.

Anuj Wadi

Technical Skills

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Languages

Python, Java, C++, TypeScript, SQL

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Core CS

Data Structures & Algorithms, OOP, System Design, Distributed Systems

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Agentic AI

MCP, Agentic Workflows, RAG, LangChain, LangGraph, Pinecone, Prompt Engineering

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Backend & Data

FastAPI, Spring Boot, REST APIs, Kafka, MongoDB, Pandas

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Cloud & DevOps

AWS, GCP, Docker, Kubernetes, Terraform, GitHub Actions, Git

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ML & Modeling

PyTorch, JAX, Transformer Architectures, LoRA/PEFT Fine-Tuning, Pandas, NumPy

Languages
Scroll to explore โ†“

Experience

AI Full Stack Engineer

PrimaThink Technologies Limited
Jan 2024 โ€” Jun 2024
  • Architected and deployed an AI-assisted Blood Bank Management System across 3 hospitals, forecasting demand using Random Forest and Gradient Boosting regressors on ~10K records.
  • Established CI/CD pipelines with automated Jest testing, reaching 85%+ coverage and cutting production bug turnaround from 2 days to under 4 hours.

Web Development Intern

PrimaThink Technologies Limited
Jul 2023 โ€” Dec 2023
  • Spearheaded an early-stage startup's 25-page responsive website from zero to launch, owning the JavaScript, React, and PHP stack end to end.
  • Drove the site from design through deployment; it has since served ~12K+ users. Promoted to AI Full Stack Engineer after the launch.

Software Engineering Virtual Program

JPMorgan Chase & Co.
Jan 2023 โ€” Jun 2023
  • Completed a self-paced JPMorgan Chase technical simulation, standing up a high-stakes project and wiring Kafka into it for real-time data streaming.
  • Connected a Spring application to an H2 database and an external REST API, and exposed a REST API within the application.

Machine Learning Intern

Tech Learn. Live
Jul 2021 โ€” Dec 2021
  • Trained and evaluated supervised learning models with Python, Scikit-learn, and TensorFlow, covering classification, regression, and neural network tasks.
  • Constructed preprocessing pipelines spanning feature engineering, normalization, and cross-validation, optimizing model accuracy across 6 ML experiments.

Education

Master of Science, Robotics and Autonomous Systems (AI)

Arizona State University
Aug 2024 โ€” May 2026
  • Pursuing advanced coursework in machine learning, computer vision, robotics, and intelligent systems with a focus on real-world autonomous technologies.
  • Engaged in hands-on projects involving AI-driven control systems, multi-agent coordination, and sensor fusion.
  • Collaborating on interdisciplinary research to develop scalable, ethical, and efficient autonomous solutions.

Bachelor of Technology, Major in Artificial Intelligence

G. H. Raisoni Institute of Engineering and Technology
Aug 2020 โ€” Jun 2024
  • Completed a comprehensive curriculum covering machine learning, deep learning, NLP, and data structures.
  • Led multiple academic projects focused on real-world AI applications, including mental health monitoring and stock price prediction.
  • Actively contributed as a project leader and grader, gaining experience in technical documentation, peer mentoring, and research-oriented development.

My Work

Multimodal AI Agent Runtime

Multimodal AI Agent Runtime

Developed a production-ready conversational AI platform with real-time speech I/O and avatar responses, achieving sub-200ms end-to-end latency on FastAPI and LLM APIs. Unified OpenAI and speech APIs behind one async FastAPI backend, supporting concurrent multi-user sessions without degrading response latency. Built with Python, FastAPI, WebSockets, Deepgram, GPT-4o, ElevenLabs, and Tavus.

Sub-200ms Latency
Harmony Logo Harmony Team
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Harmony โ€“ Mental Health Monitoring for Astronauts

Led a team of 5 to build a multimodal mental health monitoring platform on LSTM and BERT NLP pipelines, detecting distress signals across 3 data modalities. Implemented privacy-preserving infrastructure with encrypted storage and access controls, reducing per-sample inference time from 1.4s to 0.9s on biometric data. Built with Python, TensorFlow, LSTM, and BERT.

87% Accuracy
Maze Navigation

Maze Navigation with MyCobot Pro 600

Engineered an autonomous maze navigation system on ROS, OpenCV, and inverse kinematics, hitting a 92% success rate across 50+ trials and trimming collisions from 18% to 4%. Deployed a Gazebo simulation environment that eliminated the hardware dependency, shrinking iteration cycles from 3 hours on hardware to 45 minutes in simulation.

92% Success Rate
Parksnese

Parksnese - Smart Parking Solution

Developed ML-based parking prediction system with full-stack IoT solution, pitched to 3 major investors, achieving 40% reduction in parking search time.

Chalkboard AI

Chalkboard AI

Developed a fully functional website for an AI-powered chalkboard within 3 weeks, leveraging Lovable AI and OpenAI for real-time transcription and summarization to enhance student engagement.

Stock Price Predictor

Stock Price Predictor | Published Research

Engineered Q-learning model processing 50K+ daily data points for real-time trading signals, achieving 17% simulated ROI increase over six months.

Published Research
College Admission Predictor

College Admission Predictor

Built predictive analytics model using Random Forest and Logistic Regression, guiding 129+ students toward institutions with higher admission success rates.

Heart Disease Prediction

Heart Disease Prediction

Developed ML model achieving 91% accuracy using Random Forest and SVM with Apache Spark data pipeline for large-scale medical datasets.

91% Accuracy

Career snapshot

Resume

Last updated July 2026

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๐Ÿ“„ PDF format ๐Ÿ—“ Updated July 2026 โœ… ATS-friendly

Contact Me

Send a Message

Get In Touch

Feel free to contact me for any work or suggestions. I'm always open to discussing new projects, creative ideas, or opportunities to be part of your vision.

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Email
anujwadi@gmail.com
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Location
Arizona, USA โ€” Open to Relocation
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Work Authorization
F-1 STEM OPT โ€” authorized 3 years, no sponsorship required to start