Oct 2025 – Jan 2026 · 3 mos · Nashik · On-site

• Built a student-led engineering community focused on real-world, end-to-end software projects with company-level workflows.
• Designed and deployed the initial platform architecture, enabling structured project collaboration and version-controlled development.
• Launched internal engineering standards (roadmaps, PR guidelines, CI workflows) that improved contributor output quality.
• Mentored contributors across AI, backend, and frontend tracks, accelerating their ability to ship production-ready features.

Oct 2025 – Jan 2026 · 3 mos · Nashik · Hybrid

• Built a YOLO-based crop disease detection pipeline delivering 98%+ accuracy across 5 crop families, enabling faster agronomic diagnostics.
• Expanded the system from a single dataset to 5+ crop varieties, scaling the labeling and training pipeline without loss in precision.
• Improved real-world inference reliability by enhancing preprocessing and noise-handling across diverse field conditions.

Jul 2025 – Nov 2025 · 4 mos · Nasik · Remote

• Collaborated with distributed teams through structured PR reviews, issue tracking, and modular contributions.
• Strengthened project quality by writing maintainable code aligned with community standards.

Jul 2025 – Aug 2025 · 1 mo · Nashik · Remote

• Analyzed 20+ hours of American Football gameplay to derive player performance insights used for tactical adjustments.
• Generated structured performance metrics and event breakdowns that improved post-match review efficiency for coaching staff.
• Leveraged Vidswap and Coachalyze tools to speed up tagging and evaluation workflows, boosting analysis throughput by 30%.
• Earned certifications in sports analytics and evaluation, strengthening ability to convert raw footage into quantitative insights.

Jun 2025 – Jun 2025 · 0 mo · Nasik · On-site

• Selected into the competitive S-Dot batch after a technical assessment, completing a 21-day intensive program focused on Data Structures, Algorithms, and problem-solving.
• Solved structured LeetCode-style problems to strengthen algorithmic thinking, recursion, DP, and pattern recognition.
• Improved coding efficiency by practicing optimized solutions in Python and Java, emphasizing time–space tradeoffs.
• Enhanced debugging discipline and code quality through mentor-led reviews and pair-programming sessions.

May 2025 – Jul 2025 · 2 mos · Nasik · Remote

• Optimized transformer-based LLMs with TensorFlow, reducing inference time by 42% and compute usage by 18% while preserving model quality.
• Built and tuned ensemble and Random Forest models achieving 95%+ accuracy on production datasets across multiple verticals.
• Automated deployment for two production ML systems using Docker + CI/CD, increasing reliability and reducing manual downtime.
• Enhanced data pipelines by improving preprocessing, feature engineering, and quality checks to reduce model drift and training delays.

Dec 2024 – Feb 2025 · 2 mos · Nasik · On-site

• Completed a rigorous aptitude + DSA training program focused on algorithmic efficiency, competitive programming, and structured problem-solving.
• Built and optimized solutions using C++ and Python, improving speed and accuracy across mock technical evaluations.
• Applied DSA concepts to real-world-style problems, learning to break down tasks, design efficient data flows, and avoid bottlenecks.
• Participated in team coding sessions, reviews, and group problem breakdowns, improving collaboration and engineering discipline.
• Strengthened analytical and quantitative reasoning through continuous practice of logical reasoning, numerical methods, and test simulations.

Dec 2024 – Jan 2025 · 1 mo · Nasik · On-site

• Built strong foundations in quantitative aptitude, logical reasoning, and analytical decision-making through structured training and mock assessments.
• Improved time management, accuracy, and problem-solving speed across high-pressure test environments.

Oct 2024 – Jan 2025 · 3 mos · Nashik · Remote

• Contributed to open-source repositories by implementing features, fixing bugs, and improving documentation quality.
• Collaborated with distributed teams through structured PR reviews, issue discussions, and modular code contributions.

Sep 2024 – Nov 2024 · 2 mos · Nashik · Remote

• Built a YouTube Content Analyzer using CNNs, enabling multi-class video content detection with improved accuracy across diverse datasets.
• Optimized the model’s preprocessing and feature extraction pipeline to enhance robustness under varied video quality conditions.
• Integrated object-detection components to support real-time and near-real-time analysis.
• Strengthened ML engineering fundamentals while working on dataset preparation, model evaluation, and iterative tuning.

Sep 2024 – Oct 2024 · 1 mo · Nashik · Remote

• Developed four frontend projects using HTML, CSS, and JavaScript, focusing on responsive layouts, clean UI structure, and reusable components.
• Strengthened frontend fundamentals through hands-on implementation of interactive pages, state management basics, and API-driven UI features.
• Improved code quality and consistency through structured version control and modular file organization.

Aug 2024 – Sep 2024 · 1 mo · Remote

• Built four practical Python applications, including a task manager, password generator, contact management tool, and a logic-based game.
• Strengthened skills in file handling, data structures, input validation, and modular code design.
• Applied problem-solving techniques to real-world mini-projects, focusing on clarity, functionality, and user experience.
• Improved debugging, logical structuring, and code readability through consistent iteration and testing

Jun 2023 – Present · 2 yrs 11 mos · Nasik · Hybrid

• Built multiple projects across AI/ML, computer vision, agent systems, frontend engineering, and automation — covering both research prototypes and deployable systems.
• Designed Intervee, an AI-powered mock interview simulator using NLP + voice analysis, improving candidate feedback accuracy by 50%.
• Developed Stega-Shield, a full-stack steganography system supporting encrypted data hiding and secure media transmission.
• Implemented HealthPredAI, an ML-based risk prediction tool integrating tabular, text, and rule-based signals with interpretable outputs.
• Built a deep-learning crater detection model for lunar imagery (Avishkar ’24), improving geospatial crater mapping precision.
• Filed a patent related to Generative Architecture Design, focusing on automated design reasoning and multimodal generation.
• Delivered UI dashboards, automation tools, React applications, and Power BI reports used by hundreds of users.
• Gained cross-domain engineering experience by taking ideas from zero → prototype → deployment → iteration.

Aug 2022 – Present · 3 yrs 9 mos · Nashik · On-site

• Maintained strong academic performance with an 8.4 CGPA and 9.07 SGPA, consistently ranking among the top performers in the department.
• Represented the college in the Avishkar Research Competition, developing a deep-learning model for lunar crater detection and securing finalist recognition.
• Ranked Top 200 out of 68,000 participants in the TVS Analytics Challenge, demonstrating strong analytical and ML problem-solving skills.
• Achieved Top 250 in the Code Cubicle Challenge and Top 4000 in national-level competitions by Adobe and Juspay, outperforming thousands of engineering students.
• Led and delivered multiple technical sessions for juniors on AI/ML, programming, and career guidance, supporting skill development for 300+ students.
• Actively mentored peers on projects, technical concepts, and roadmaps, contributing to a collaborative and growth-focused academic environment.