ANUJ WADI
SWE & AI Engineer
Who am I?
Anuj Wadi is an AI Engineer and Robotics graduate of Arizona State University, passionate about building intelligent systems that combine Generative AI, Machine Learning, and Autonomous Systems to solve real-world problems. With experience in AI infrastructure, multimodal systems, and production-grade software, he specializes in developing scalable AI-driven applications that bridge cutting-edge research with practical deployment. Anuj is focused on leveraging Large Language Models, Computer Vision, and intelligent automation to create impactful solutions across healthcare, finance, and robotics.
Technical Skills
AI Systems & Agents
LLM applications, RAG pipelines, prompt engineering, fine-tuning (LoRA/PEFT), multimodal AI, quantitative modeling
Languages
Python, SQL, MATLAB, R, JavaScript, TypeScript, C++
Full Stack
FastAPI, Node.js, REST APIs, React, production deployment, user-facing applications
Data & Infrastructure
MongoDB, Redis, Apache Kafka, data engineering, large-scale & multimodal datasets
Cloud & MLOps
Docker, Kubernetes, AWS, GCP, CI/CD (Jenkins), Git, Unix/Linux
AI/ML Frameworks
PyTorch, TensorFlow, Scikit-learn, OpenCV
My Work
Multimodal AI Agent Runtime
Launched a public-facing conversational AI platform with real-time speech I/O and avatar responses for 10,000+ users. Integrated LLM APIs, speech recognition, and text-to-speech into a unified FastAPI backend, reducing response latency by 40%.
Harmony โ Mental Health Monitoring for Astronauts
Directed a team of 5, building a multimodal wellness platform with LSTM/BERT NLP pipelines, achieving 87% accuracy in distress detection. Delivered HIPAA-compliant infrastructure using Python and TensorFlow, cutting data processing time by 35%.
Maze Navigation with MyCobot Pro 600
Engineered an autonomous navigation system using ROS, OpenCV, and inverse kinematics; achieved 92% success rate and 78% collision reduction. Deployed a Gazebo-based simulation environment, accelerating iteration cycles by 3x.
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
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 | Published Research
Engineered Q-learning model processing 50K+ daily data points for real-time trading signals, achieving 17% simulated ROI increase over six months.
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
Developed ML model achieving 91% accuracy using Random Forest and SVM with Apache Spark data pipeline for large-scale medical datasets.
Experience
Work Experience
AI Full Stack Engineer
- Architected an AI-assisted Blood Bank Management System using JavaScript, PHP, MongoDB, and REST APIs with RFID-based tracking across 3 hospital workflows.
- Optimized database queries and backend automation processes, achieving a 46% increase in system efficiency and reducing manual processing time by 30%.
- Spearheaded CI/CD pipelines with automated Jest testing, achieving 85%+ test coverage and slashing debugging time by 75%.
Software Engineering Intern
- Constructed a real-time data pipeline using Python, Kafka, Pandas, and Scikit-learn, sustaining 10,000+ events/sec with sub-100ms latency.
- Accelerated 5 ML pipeline prototypes to production, cutting deployment time by 35% and rollback incidents by 20%.
- Containerized applications via Docker, Kubernetes, and Jenkins, reducing infrastructure setup time by 51% across 4 microservices.
Machine Learning Intern
- Designed and delivered 6 ML workshops using Python, TensorFlow, and PyTorch, training 530+ students across 4 institutions.
- Produced an AI/ML curriculum covering data preprocessing, neural networks, and model evaluation, adopted by 3 university programs.
- Designed and executed AI outreach campaigns, extending reach to over 1,000 students and elevating event participation by 40%.
Education
Master of Science, Robotics and Autonomous Systems (AI)
- 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
- 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.
Career snapshot
Resume
Last updated May 2026
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Contact Me
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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.