
Dhruv Jindal
@dhruvjindal1
I build LLM-powered applications, machine learning pipelines, and scalable backend systems.
What I'm looking for
I've built AI and ML systems at CSIR-CSIO, Infosys Springboard, and Gokaddal Technologies, from automated gait analysis to content optimization and scalable backend APIs. At CSIR-CSIO, I processed 11,000+ gait cycles and implemented anomaly-detection models with approximately 99% agreement.
I also build production-minded AI products, including an AI learning platform supporting 1,000+ concurrent users and a customer-segmentation dashboard trained on 1M+ retail transactions. I work across Python, SQL, LLMs, machine learning, APIs, analytics, and deployment-focused software systems.
Experience
Work history, roles, and key accomplishments
AI/ML Research Intern
CSIR-CSIO
Jan 2026 - May 2026 (4 months)
Built a Python-based automated gait analysis pipeline using Xsens 17-IMU data, processing 11,000+ gait cycles. Implemented One-Class SVM and Isolation Forest models for unsupervised gait anomaly detection, achieving ~99% model agreement.
AI Intern
Infosys Springboard Internship
Sep 2025 - Dec 2025 (3 months)
Architected an end-to-end AI content optimization pipeline integrating LLM-based generation, adaptive prompting, trend scoring, and multi-layer sentiment analysis, improving content relevance and quality by 45%. Automated A/B variant evaluation and model retraining using Random Forest, GridSearchCV, and SMOTE, reducing manual analysis effort by 60%.
Software Engineering Intern
Gokaddal Technologies
Jun 2025 - Aug 2025 (2 months)
Optimized core backend APIs and frontend modules for a global website portal, enhancing scalability and maintainability. Owned features across the full software development lifecycle, coordinating with cross-functional teams to achieve 100% on-time delivery.
Education
Degrees, certifications, and relevant coursework
Punjab Engineering College
B.Tech, Electrical Engineering
2023 -
Grade: 7.35
Pursuing a B.Tech in Electrical Engineering with a CGPA of 7.35, expected to graduate in the future.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Salary expectations
Skills
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