# Aishwarya Malgonde > Senior Software Engineer | Applied AI, NLP Location: San Diego, California, United States Profile: https://flows.cv/aishwaryamalgonde Hello! I'm a Computer Science Master's student at UMass Amherst, graduating in May 2024. I have about six years of experience in developing, deploying, monitoring and maintaining AI solutions for various domains, such as healthcare, insurance, automotive and more. I have a strong background in computer vision, natural language processing, networking, and cloud/GPU computing, and I'm proficient in Python, AWS Services (EC2, S3, DynamoDB, ELB, OCR, VPN, IAM), Flask and Docker. I like to stay updated with the latest research and innovations. I have a research-oriented mindset and I have published and presented at a conference on transportation engineering. I have also received multiple scholarships and awards for my academic excellence and research contributions. I'm eager to learn and collaborate with other AI/ML enthusiasts, and I'm open to connecting for opportunities or idea sharing. ## Work Experience ### Senior Software Engineer @ Highmark Health Jan 2024 – Present | San Diego, California, United States ### Graduate Student Researcher @ Microsoft Jan 2024 – Jan 2024 | United States We conducted an extensive evaluation of small language models for their effectiveness in extracting entities and relations to generate knowledge graphs from text corpora. Our assessment included models like Phi-2/3 by Microsoft and Gemma by Google, with a particular focus on various prompting techniques. The primary objective was to compare their performance against leading models such as LLaMA2 and Mistral, as well as large language models (LLMs) like GPT-4. ### Deep Learning Engineer @ Silvernox Tech Ventures Jan 2020 – Jan 2022 | Mumbai Automated claims assessment using AI for automotive and travel insurance industry Car Insurance - Processed ~5 Million images for multiple deep learning tasks 1. Trained, tested and integrated an ensemble of instance segmentation (MaskRCNN), semantic segmentation (UNET) and object detection (SSD) models, for damages (>90% accuracy) and part detections (>97% accuracy) 2. Trained classification models in Keras with focal loss to handle unbalanced dataset, inorder to classify car model (>95% accuracy), color (>90% accuracy) and damaged parts (>80% accuracy) 3. Deployed 15 deep learning models on TensorFlow serving for efficient inference and dockerized it for scaling 4. Engineered the Flask back-end of the product and integrated it with serving and react using http requests 5. Solely generated a codebase of 100 scripts and 20,000 lines of code from scratch 6. Integrated AWS optical character recognition APIs to parse VIN number, registration and license plates 7. Developed YOLO object detection model for odometer reading in seven-segmentdigitformat 8. Incorporated databases like Redis, AWS S3 and AWS Dynamodb for data storage and retrieval on the fly 9. Configured Supervisor, Gunicorn, Redis Queue and Nginx to manage processes during production Travel Insurance 1. Achieved a 100% accuracy on claim settlement amount without training any deep learning model 2. Extracted text from customer tickets, refunds and bank documents using AWS OCR apis 3. Compiled customer, travel and payment information from each document using text mining techniques ### Deep Learning Consultant @ Nanonets Jan 2020 – Jan 2020 | Mumbai Area, India Provided API as a Service for customers in FMCG, Finance and Oil & Gas Industries 1. Trained object detection models to solve customer requests like logo detection, invoice digitization, implants detection, person counter, text extraction, pipeline leakage detection and rust detection 2. Programmed the business domain workflow in flask rest-apis and hosted them on AWS and GCP instances ### Machine Learning Engineer @ Tata Centre for Technology and Design, IIT Bombay Jan 2018 – Jan 2020 | Mumbai Area, India ‘GynaeCam’ - A low-cost cervical cancer screening device with ML aided clinical workflow 1. Built object detection (80 mAP) and image classification (75% accuracy) models using TensorFlow and Keras APIs, to localize cervix and classify it into stage 1 versus stage 2 of cervical pre-cancer respectively 2. Optimized the models using TensorFlow Lite for integration in the android application 3. Studied 30+ research papers to get more insights of the problem space and pre-processing approaches 4. Led a team of five, to build a full-stack integration with deployment of AI Built a full-stack integration for deployment of AI, along with image classification and object detection models in ipython on Keras and Tensorflow. Implemented both of the above models in an android app through Tensorflow Lite. Studied 30+ research papers to deep dive and get more insights of the problem space. Frequently field tested the hardware device and the android app for feasibility Uterine cervix image segmentation to detect pre-cancer - ML/AI - Computer Vision - Deep Learning - Tensorflow 2.0 - Python - OpenCV - CUDA ### AI Engineer @ Digital Product School by UnternehmerTUM Jan 2019 – Jan 2019 | Munich Area, Germany Collaborated with City of Hamburg to develop a software based solution to get real-time information on construction sites in the city to manage the traffic flow effectively. Built a Construction Site Detector model on Keras and Tensorflow in Python. Built a pipeline to send live images and location of the detected construction site. ### Experienced Associate @ PwC Jan 2017 – Jan 2018 | Mumbai Area, India PwC Deals & Innovation Technology - Worked on over 30 deals were we helped the clients make acquisition, divestiture, or strategic alliance by providing a unique combination of financial, commercial and operational insight. We are delivering unparalleled knowledge which is highly valued in the market today. ### Associate @ PwC Jan 2016 – Jan 2017 | Mumbai Area, India Worked for clients in financial services sector and worked on projects involving anomaly detection, customer experience and model validation. Applied techniques like bayesian networks, isolation forest and page rank. Created a package in R to run dynamic bayesian networks. ### Institute Student Mentor @ Indian Institute of Technology, Bombay Jan 2015 – Jan 2016 I was nominated from 351 applicants based on strong peer review, all-round skills and accountability. During my tenure I have mentored a batch of 10 freshmen in their academic and extracurricular endeavours . ### Research Assistant @ University of Calgary Jan 2015 – Jan 2015 | Calgary, Canada Area Work acknowledged in the research paper: 'Variable speed limit: A microscopic analysis in a connected vehicle environment' Publication Link - http://www.sciencedirect.com/science/article/pii/S0968090X15002648 Scholarship: Received the prestigious MITACS Globalink Scholarship for carrying out research in Intelligent Transportation Systems. Contribution: SHORT-TERM TRAFFIC STATE ESTIMATION ON FREEWAYS | Prof. Lina Kattan 1. Developed a trajectory estimation model for a system consisting of both unequipped and smart cars 2.Investigated and simulated existing theoretical models, Weidemann and Newell’s model, in MATLAB ### Research Assistant @ Indian Institute of Technology, Bombay Jan 2014 – Jan 2014 | Mumbai Area, India Impact: 1. Co-authored a research paper, Sreekumar, M., Malgonde, A., and Mathew, T., ‘Numerical experiments on a continuum traffic flow model to demonstrate the (in)appropriateness of flux functions’ and presented at Conference of Transportation Research Group of India, 2015 2. Co-authored a research paper, Sreekumar, M., Malgonde, A., and Mathew, T. V., ‘Applicability of continuum models with bi-regime flux function for dynamic travel time predictions’, presented at TPMDC, 2014 and accepted for publication in Transportation Research Procedia, 2015 Contribution: REAL TIME TRAVEL TIME PREDICTOR 1. Developed a travel time estimation model for vehicles in Indian traffic conditions 2. Simulated Godunov, Mac Cormack, Upwind, Lax Friedrichs and Lax Wendroff numerical schemes and implemented them in LWR model and AR model in C and python. 3. Established the potential of macroscopic model for modelling in Intelligent Transportation System ## Education ### Master's degree in Computer Science University of Massachusetts Amherst Jan 2023 – Jan 2024 ### Bachelor’s Degree in Engineering Indian Institute of Technology, Bombay Jan 2012 – Jan 2016 ## Contact & Social - LinkedIn: https://linkedin.com/in/amalgonde --- Source: https://flows.cv/aishwaryamalgonde JSON Resume: https://flows.cv/aishwaryamalgonde/resume.json Last updated: 2026-03-22