Varun Choudhary
@varunchoudhary
AI / Machine Learning Engineer | Applied ML, Computer Vision, LLMs | Ex-Data Science Intern @ Tech Mahindra
What I'm looking for
I am a driven software engineering professional with strong foundations in algorithms, systems design, and modern development practices, focused on delivering production-ready ML and automation solutions.
I have hands-on experience building real-time perception systems, quantitative trading strategies, and robust automation tools—several efforts resulted in peer-reviewed publications and measurable performance gains (for example, trajectory MAE 0.45m, speed MAPE ±1.8 km/h, and a trading strategy that outperformed the S&P 500 benchmark by 15%).
I collaborate across teams, lead cross-functional initiatives, and prioritize reliability and scalability in the SDLC; I seek roles where I can apply ML, systems engineering, and automation to deliver impactful products in production environments.
Experience
Work history, roles, and key accomplishments
Researcher — TrajecTrack
SRM Institute of Technology
Developed a real-time trajectory estimation system for autonomous vehicles (33 FPS) achieving 0.45m MAE, ±1.8 km/h speed MAPE, and 94.1% lane detection accuracy using LiDAR–camera fusion and YOLOv8.
Data Science Intern
Gained hands-on experience in machine learning workflows and data analysis, using Firebase and Microsoft Power Apps to support ML pipeline development and prototyping during a structured internship.
Automation Engineer — Projects
Independent Projects
Built a Selenium-based booking automation with 95% success across 10+ workflows and designed 30+ API test cases achieving 100% endpoint coverage, reducing manual QA by 80%.
Researcher — Road Accident Prediction
SRM Institute of Technology
Developed CNN-based hazard detection achieving 90% accuracy and integrated OpenCV pothole detection with Mask R-CNN for multi-object segmentation and real-time traffic sign recognition.
Researcher — Algorithmic Trading
SRM Institute of Technology
Built quantitative trading and portfolio optimization models on S&P 500 data that outperformed the benchmark by 15% and reduced portfolio volatility by 20% using Modern Portfolio Theory and Monte Carlo simulations.
Machine Learning Engineer — Anomaly Detection
Independent Projects
Developed an ANN-based credit card fraud detection system with 98% detection rate, applied SMOTE to address class imbalance and reduced false positives by 15%.
Education
Degrees, certifications, and relevant coursework
SRM Institute of Technology
Bachelor of Technology, Computer Science and Engineering
Grade: 7.57 CGPA
Activities and societies: Committee Head at AARUUSH (Jul 2022–Jul 2023); internships and research publications in autonomous vehicles and algorithmic trading.
Completed a B.Tech in Computer Science and Engineering with coursework in algorithms, OS, DBMS, AI, and machine learning; involved in research projects on trajectory estimation and trading systems.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Portfolio
varun-portfolio-f1.netlify.appJob categories
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