# Kruthi Ninga Raj > Software Engineer Location: San Jose, California, United States Profile: https://flows.cv/kruthi Machine Learning Enthusiast and Globe-Trotter! 👩🏻‍💻🗺️ Passionate about automating the future and predicting the unknown, I work at the crossroads of machine learning, data science, and computer vision to turn data into futuristic and valuable insights. 🔍 Looking for: Full-time opportunities in Software Engineering, Machine Learning, Data Science, or Data Analysis. 🏕️ Beyond Algorithms: When I'm not diving into data, you'll find me traveling, hiking, exploring nature, and marveling at marine animals. 📬 Reach out: knrajapp@gmail.com ## Work Experience ### Software Engineer @ Acnovate Corporation Jan 2025 – Present | San Jose, California, United States ### Software Engineer Intern @ Xiphoid Inc Jan 2025 – Jan 2025 ### Graduate Intern @ Syracuse University College of Engineering and Computer Science Jan 2024 – Jan 2025 • Built and deployed machine learning models to recommend recipes using structured data (user preferences, dietary tags, ingredient vectors), improving personalization and engagement. • Designed a content-based filtering system using cosine similarity and feature encodings (TF-IDF, one-hot, scaled nutrition scores) to generate top-N recipe suggestions. • Developed modular training pipelines in scikit-learn and automated preprocessing workflows for feature generation, normalization, and input validation. • Implemented offline evaluation pipelines using metrics such as precision, recall, and coverage, and conducted A/B testing to benchmark different filtering strategies. • Created interactive dashboards using Power BI to track model performance, ingredient frequency, and user interaction patterns, enabling real- time feedback for iterative model tuning. • Ensured data quality by implementing validation checks and schema consistency rules during data ingestion, increasing model stability and trustworthiness. • Focused on reproducibility and scalability by maintaining clean code, consistent documentation, and experiment tracking for all modeling iterations. ### Academic Tutor @ Syracuse University Jan 2023 – Jan 2024 • Tutored students in core programming concepts using Java and Python, covering topics like control flow, OOP, recursion, and file handling. • Provided guidance on solving algorithmic problems related to arrays, linked lists, trees, graphs, and dynamic programming. • Conducted weekly problem-solving sessions to build proficiency in time and space complexity analysis. • Mentored students in preparing for technical interviews by teaching structured approaches to coding challenges on platforms like LeetCode. • Reviewed student code for correctness, efficiency, and readability, promoting best practices in clean coding and debugging. ### Software Engineer Intern @ Bosch India Jan 2021 – Jan 2021 •Developed a computer vision system to identify, count, and measure industrial components in a supply chain setting, including screws, bolts, and cylindrical parts like ball bearings. •Implemented object detection using classical image processing and contour-based techniques for small part segmentation. •Extracted geometric features (diameter, length, area) using calibrated imaging methods to ensure precise measurement for quality control. •Automated inventory verification by counting parts on trays and conveyor belts with high accuracy. •Designed a pipeline to handle varying lighting conditions, orientations, and occlusions in real-world industrial settings. •Conducted experiments to validate measurement precision. ### Software Engineer Intern @ Integrated Systems Jan 2021 – Jan 2021 •Established a computer vision–based quality inspection framework to automatically detect and segregate visually defective products in a manufacturing workflow. •Built and trained Convolutional Neural Network (CNN) models for steel surface defect detection and industrial welding defect classification using supervised learning techniques. •Performed image preprocessing, noise reduction, contrast enhancement, and data augmentation to improve model robustness. •Implemented defect localization and contour detection using traditional image processing techniques in OpenCV. •Applied transfer learning using pre-trained architectures (e.g., ResNet, VGG) to improve classification accuracy on limited industrial datasets. •Achieved ~92–95% classification accuracy across multiple defect categories, reducing manual inspection time and improving defect detection consistency. •Deployed a prototype inference pipeline for near real-time defect identification in a simulated production setting. ### Software Engineer Intern @ Bosch India Jan 2021 – Jan 2021 •Developed and deployed end-to-end ML solutions for predictive maintenance of diesel engines, enabling proactive detection of component failures and improved fleet reliability. •Designed robust feature pipelines using multivariate sensor logs from ECU telemetry (INCA and DiagRA) to generate engine health scores and predict remaining useful life using XGBoost and Random Forest models. •Automated ETL workflows to ingest, clean, and transform raw telemetry data into structured data source, reducing manual preprocessing effort by 80%. •Achieved improvement in failure detection and maintenance scheduling accuracy, significantly reducing unplanned downtime and lowering service costs for enterprise fleet clients. •Implemented monitoring dashboards and reporting tools to track model performance and facilitate data-driven maintenance decisions. ## Education ### Master's degree in Computer Science Syracuse University College of Engineering and Computer Science ### Bachelor of Engineering - BE in Computer Science & Engineering Visvesvaraya Technological University ## Contact & Social - LinkedIn: https://linkedin.com/in/kruthiraj --- Source: https://flows.cv/kruthi JSON Resume: https://flows.cv/kruthi/resume.json Last updated: 2026-04-10