# Ajeenckya M. > Machine Learning Engineer | LLM Integrations | AI Agents | Deep Learning | Uncertainty Modeling Profile: https://flows.cv/ajeenckya I am a Machine Learning Engineer building end-to-end AI systems that combine probabilistic modeling, deep learning, and optimization. My work spans training and inference pipelines, feature engineering, and model evaluation with real data. I have designed and implemented ML systems integrating advanced models (including LLM-derived features) with structured and environmental datasets, achieving measurable improvements in accuracy, calibration, and robustness. I am passionate about delivering scalable ML solutions with strong performance and real-world impact. Currently completing my M.S. in Industrial & Systems Engineering with a focus on ML & AI at the University of Wisconsin–Madison and actively seeking Machine Learning or AI Engineer opportunities where rigorous modeling meets production systems. ## Work Experience ### Graduate Teaching Assistant / Grader @ University of Wisconsin-Madison Jan 2026 | Madison, Wisconsin, United States • Supported a graduate machine learning course by helping students build, debug, and evaluate models in Python using real-world datasets. • Provided detailed technical feedback on assignments and projects involving feature engineering, model training, and performance evaluation. ### Graduate Student Research Assistant @ University of Wisconsin-Madison Jan 2025 Built a probabilistic forecasting pipeline combining historical, weather, and LLM-extracted news signals for outcome prediction. Developed a FastAPI inference service that converted real-time news into structured features, improving calibration by 12%. Built XGBoost weather-impact models across temperature, humidity, and precipitation, reducing scenario variance by 17%. Added a Bayesian output layer to model uncertainty, improving calibration by 15% and reaching a Brier score of 0.176 with 67% accuracy. Improved dominant-outcome recall from 82% to 84% while reducing overconfident predictions in uncertain cases. ### Graduate Apprentice Trainee @ Fiat India Automobile Private Limited. Ranjangaon. Jan 2023 – Jan 2024 | Pune, Maharashtra, India • Designed a regression-based model to analyze cycle time data, identifying bottlenecks and predicting station delays. • Transformed unstructured worker logs into structured datasets, enhancing data-driven analysis capabilities. • Developed standardized data pre-processing pipelines for consistent data collection, improving reliability across teams. ### Maintenance Engineer @ Powertrac Tractors Jan 2022 – Jan 2023 | Maharashtra, India Trained and mentored multiple technician teams by formalizing critical maintenance procedures into standardized, repeatable workflows, ensuring safe, consistent, and low-error execution across mechanical systems. Planned and managed preventive and corrective maintenance schedules, analyzing failure patterns to minimize downtime and improve overall system reliability. Redesigned the maintenance shop layout as a process optimization problem, improving workflow efficiency and accessibility, and reducing maintenance lead times while increasing technician productivity by 12%. Designed and validated custom diagnostic gauges and jigs to improve measurement accuracy and alignment, reducing manual error rates and enabling reliable, high-quality diagnostic signals during tractor servicing. ### Radio Frequency Engineer @ Amdocs Jan 2022 – Jan 2022 | Pune, Maharashtra, India • Designed and drafted fiber optic network layouts for the Southeast U.S. region using Aramis and AutoCAD software, ensuring precise routing and optimized infrastructure for RF communication. • Ranked top in training, completing all assigned design tasks faster than peers with 100% accuracy, demonstrating strong technical aptitude and rapid learning in telecom infrastructure planning. ### Graduate Engineer @ Tata Motors Jan 2021 – Jan 2022 | Pune, Maharashtra, India Led new product process planning and full shop redesign for integrating two SUV models, coordinating with cross-functional teams to optimize layout, line balancing, and resource allocation as a system-level optimization problem, improving efficiency by 18%. Directed daily operations for contract teams by assigning tasks, validating process configurations, and monitoring execution, ensuring smooth ramp-up during SOP and beta builds across vehicle and powertrain assembly lines. Recognized with a Kaizen Award for designing a custom palletization system that improved logistics safety and reduced engine handling costs by 20%, demonstrating data-driven process innovation. Conducted digital tool validation, ergonomic analysis, and iterative process refinement, using quantitative performance metrics to achieve a 15% improvement in Jobs Per Hour (JPH) while maintaining safety and product quality. ## Education ### Master of Science - MS University of Wisconsin-Madison ### Bachelor of Engineering - BE Shivaji University ## Contact & Social - LinkedIn: https://linkedin.com/in/ajeenckya-mahadik - Portfolio: https://ajeenckya5.github.io - Email: mailto:avmahadik@wisc.edu --- Source: https://flows.cv/ajeenckya JSON Resume: https://flows.cv/ajeenckya/resume.json Last updated: 2026-04-17