# Anushka Sandesara > Software Development Engineer II - Amazon Bedrock | MSE Data Science -UPenn | Research Scientist-The Wharton School | Ex-ISRO Location: New York, New York, United States Profile: https://flows.cv/anushkasandesara M.S. in Data Science | University of Pennsylvania | GPA: 3.97/4.0 | Outstanding Service Award B.Tech. in Computer Engineering | Charotar University of Science and Technology | GPA: 4 Reviewer: EMNLP 2023 I am Anushka Sandesara, a data scientist and AI engineer passionate about building solutions that bridge data, intelligence, and impact. I am deeply fascinated by Machine Learning, Artificial Intelligence, Natural Language Processing, and the infrastructure that powers scalable AI systems. Currently, I work on AWS Bedrock, designing and deploying Nova foundation models across multiple regions, ensuring scalable, secure, and high-performing infrastructure for global AI workloads. My work enables organizations to harness next-generation generative AI safely and efficiently. Previously, I contributed as a Software Development Engineer at AWS Aurora, a Research Assistant at Wharton, and an ML Researcher at ISRO, working on innovative data-driven projects and AI research initiatives. I thrive at the intersection of technology, research, and real-world impact, and I’m always excited to tackle new challenges, collaborate with forward-thinking teams, and deliver solutions that truly make a difference. ## Work Experience ### Software Development Engineer II - Amazon Bedrock | AWS Generative AI | Amazon Nova Models @ Amazon Web Services (AWS) Jan 2026 – Present | New York, United States ### Software Development Engineer I - Amazon Bedrock | AWS Generative AI | Amazon Nova Models @ Amazon Web Services (AWS) Jan 2024 – Jan 2026 | New York, United States • Working on AWS Bedrock infrastructure to host and operationalize Nova foundation models across multiple AWS regions • Designed and implemented scalable, secure infrastructure solutions to enable reliable regional model launches and high availability • Collaborated with cross-functional teams to ensure launch readiness, performance, and operational excellence for production AI workloads • Built and maintained deployment pipelines and infrastructure components, following AWS best practices for reliability, scalability, and fault tolerance ### Software Development Engineer I | AWS RDS Aurora | SQL & PostgreSQL Performance Engineering @ Amazon Web Services (AWS) Jan 2023 – Jan 2024 | East Palo Alto, CA • Worked with AWS Aurora Performance Data Service team to optimize database performance, leveraging expertise in both Aurora SQL and PostgreSQL • Designed and implement solutions to enhance query efficiency and throughput, ensuring seamless operation of data-intensive applications • Developed and maintain database schemas, queries, and stored procedures, adhering to best practices for reliability and scalability ### Machine Learning Engineer @ Gisual Jan 2023 – Jan 2023 | King of Prussia, Pennsylvania, United States • Developed and tested machine learning models for core problem-solving and customer insights. • Managed the end-to-end process, from selecting and preparing datasets to training and retraining models as required. Took a lead role in designing the machine learning engineering infrastructure, ensuring a robust and scalable framework for model deployment and maintenance. • Explored and implemented innovative applications of machine learning within the business context. ### Graduate Teaching Assistant @ University of Pennsylvania Jan 2022 – Jan 2023 | Philadelphia, Pennsylvania, United States •Teaching Assistant to Professor Susan Davidson for CIS550 Databases and Information Systems •Key responsibilities include holding office hours and recitations, grading assignments, Beta Course Testing on Coursera and responding to student queries via Piazza. ### Graduate Research Assistant @ The Wharton School Jan 2022 – Jan 2023 | Philadelphia, Pennsylvania, United States Working at Environmental, Social, and Governance (ESG) Analytics Lab & Political Risk Lab under the guidance of Dr. Witold Henisz with the aim of analysing the influence of businesses on the political and social landscape. ### Software Development Engineer Intern @ Amazon Jan 2022 – Jan 2022 | Seattle, Washington, United States Team: AWS Kinesis Data Streams • Analyzed log metrics for the team, specifically focusing on aggregating metrics from customer-initiated Put Records API calls. • Additionally, addressed the challenge of redundant metrics within the system, which were consuming excessive Timber space. • Developed a system to efficiently identify and remove redundant metrics, ensuring streamlined data storage while retaining comprehensive aggregated metrics for the team, thereby optimizing overall system efficiency. ### Graduate Teaching Assistant @ University of Pennsylvania Jan 2021 – Jan 2022 | Philadelphia, Pennsylvania, United States •Teaching Assistant to Professor Eleanor Tecosky-Feldman for MCIT 594 Data Structures and Software Design •Key responsibilities include holding office hours and recitations, grading assignments, Beta Course Testing on Coursera and responding to student queries via Piazza. ### Chapter Lead @ Omdena Jan 2021 – Jan 2021 | Pennsylvania, United States The Official Chapter of Omdena in Pennsylvania, USA ### Machine Learning Engineer @ Omdena Jan 2021 – Jan 2021 | New York, United States • Clinical studies, like clinical trials and observational studies, assess whether a drug intervention is effective for treating a disease. Many clinical studies have evaluated non-cancer generic drugs to treat cancer. • Reboot Rx is interested in synthesizing information from publications describing these studies in order to identify the most promising repurposing opportunities. • The project's goal is to automatically extract these values and store them in a structured format for analysis using NLP. ### Junior Machine Learning Engineer @ Omdena Jan 2020 – Jan 2021 | New York, United States • Improve the quality of case management on both cost and time efficiency • Dynamically analyze data and better organize intervention in real-time to avoid unnecessary delays in service • Leverage collective organizational knowledge from present and past practice • Unify and standardize expert guidance to field workers worldwide • Design individualized solutions to individual problems of children and families as a result of migration across international borders ### Machine Learning Research Intern @ ISRO - Indian Space Research Organization Jan 2021 – Jan 2021 | India •Worked on Convolutional Neural Network (CNN) time series-based image prediction technique for fog nowcasting with INSAT-3DR data for night time, for a very dense fog spell. •Implemented data acquisition and conventional brightness temperature difference method to identify fog during night time in the satellite images. •The error percentage for predicting the exact next image (15 minutes) is approximately between 5-8% while the error increases when prediction is performed within the 2-hour range to 10 -12%. ### Machine Learning Team @ AWS Students Club ( ASC Charusat) Jan 2020 – Jan 2021 •Provided a platform for all the interested students to learn about AWS and other cloud services •Machine Learning projects that help the club to prosper effectively •Various webinars and coding events Link:- https://asc.charusat.ac.in/ ### Machine Learning Interestship @ Clique Jan 2020 – Jan 2021 •Worked on a basic Mentor-Mentee recommendation engine, which is capable of understanding users history and preferences to recommend a mentor to mentee and a mentee to mentor by continuously updating feedback and outcomes into the recommendation engine •Developed a basic conversational AI that talks to mentors and mentees to figure out what their needs are, what kind of help they want to offer and do all sorts of information collection, from a chat interface ### Data Science Intern @ The Sparks Foundation Jan 2020 – Jan 2020 | Singapore •Worked on Projects related to Data Analysis and Machine Learning• •Completed Stock Market Prediction of SENSEX using Numerical and Textual Analysis ### Data Science Intern @ Exposys Data Labs Jan 2020 – Jan 2020 | Bengaluru, Karnataka, India •Worked on machine learning and artificial intelligence projects as well as upskilled my data science skills. •Looked over analysis of customers and developed customer segmentation project for the company •Gained knowledge of how K-means clustering an unsupervised machine learning technique is implemented ### Research Intern @ CHAROTAR UNIVERSITY OF SCIENCE AND TECHNOLOGY Jan 2020 – Jan 2020 •Worked on a research project named "A Comparative Study on Speech Emotion Recognition". •Studied various techniques thoroughly (MLP, SVM, CNN, RNN-LSTM, ConvLSTM) •Developed a comparison table including the strength and weaknesses of the techniques in existence. ### Intern @ Anstel Pty Ltd Jan 2019 – Jan 2019 | Gurgaon, India •Exploring Python and visualization of datasets •Implementing face recognition using python and OpenCV •Tried to gain more accuracy in the recognition system ## Education ### Master's degree in Data Science University of Pennsylvania ### Bachelor of Technology - BTech in Computer Engineering CHARUSAT ### Standard 12th - 85%(PCM) St. Xavier's High School ### Standard 10 Som Lalit School - India ## Contact & Social - LinkedIn: https://linkedin.com/in/anushka-sandesara - Website: https://anushkasandesara.medium.com/ - Website: https://github.com/anusandesara - Website: https://anusandesara.github.io/ --- Source: https://flows.cv/anushkasandesara JSON Resume: https://flows.cv/anushkasandesara/resume.json Last updated: 2026-04-05