Govind Sri Rengarajan Email & Phone Number

Sydney, New South Wales, Australia

Sydney, New South Wales, Australia

• Worked as a MLOps Engineer for a client of Servian• Created an inference CI/CD pipeline for the client that had multiple deep learning based models to be deployed for inference• Used Amazon AWS Sagemaker, Step functions, Lambda, S3 and ECR to create the inference pipeline• Configured and used a docker image that would eventually be used in the pipeline• Write Lambda function using Python and use AWS data science sdk (using python) for creating the stepfunction• Configure the right AWS instance type depending on the purpose of use• Perform an end-to-end testing of the entire pipeline to ensure everything worksTechnology used as a part of Servian: Python, AWS Sagemaker, Stepfunction, Lambda, S3, ECR, docker

Melbourne, Victoria, Australia

Responsibilities – Machine Learning Engineer:• Research, design and develop a new pipeline for an upcoming feature for the product using Python, Tensorflow, Keras• Performed Unit and regression testing on the new feature• Adhere to CI/CD pipeline and other solid software engineering principles• Write corresponding Lambda functions on the AWS cloud that handles the REST API requests using Python, AWS SAM framework• Work effectively within an Agile cross-functional team scattered across the globe• Been involved in setting up and modifying the pipeline that does image preprocessing, model training, model evaluation, deploying the model in S3 bucket for the use by customers, other stakeholdersResponsibilities – Data Scientist:• Worked as a part of R&P team with the major task to understand the implications of the model, improve its accuracy and include it as a part of production pipeline• Implement new and emerging techniques from different scientific publications and perform experiments to analyze the results qualitatively and quantitatively• Modify the neural network architecture to improve the accuracy of the model• Perform various experiments on numerous problems, hypothesis involved in improving the accuracy of the model, dealing with memory constraints etc. Setting up the experiments, analyzing the results, reporting to peers, implementing the changes accordingly

Melbourne, Victoria, Australia

● Design and develop new features of Zetaris Cloud Data Fabric in Scala● Research, analyze, contribute to the functional and technical design, implement the cache functionality by leveraging Apache Ignite for Zetaris Lightning application using Scala and SQL. Brought down the query execution time on the tables containing millions of records by almost 50%● Ensure the solution meets the functional and technical specification according to organizational quality standards● Write unit-test cases, conduct test-case and peer code reviews for the implemented functionality● Build, package, integrate the functionality into Zetaris Lightning application and deploy the application● Create and maintain the technical project documentation for the implemented functionality● Work effectively within an Agile cross-functional team. Actively engaging and contributing to the continuous improvement of Agile, lean process and practices

Melbourne, Victoria, Australia

• Identifying appropriate visual datasets to train the deep learning based model. Choose appropriate images after thorough analysis of the end use-case, create label file for the same as per Xailient accepted standards using python.• Use Xailient sdk containing the model to develop the computer vision applications. Wrote clean and re-usable code using Python and OpenCV.• Generate insights and perform various machine learning/deep learning/data science experiments to evaluate the performance of the model and optimize it, when needed.• Compare different object detection solutions by training the deep neural networks from the scratch and analyze their accuracy (mAP) and inference times on different datasets. Build models using Tensorflow Object Detection API using Python, Tensorflow. Training the model in an AWS EC2 instance with GPU.• Work as a part of the R&D team to assist the CTO by conducting research, experimentation, documentation of other similar open source computer vision products. Using their pre-trained models to derive insights for comparison.• Develop a MobileNetV2 based deep learning model from the scratch using keras and tensorflow backend. Train the model on huge datasets like ImageNet having over a million images. The model was developed for research purpose to compare it with custom Xailient models.

Melbourne, Australia

• Analyzing, cleansing and verifying the integrity of the customer's data coming in from the leading freight carriers in Australia before being fed into the internal system.

Perth, Western Australia, Australia

• Gather requirements from the stakeholders.• Understanding the requirements and going through the changes in the data structure in the backend and critically formulate and evaluate a new design.• Understanding the code and formulating changes to the application.• Using ASP. Net, C#, Razor, LINQ, Javascript, JQuery, HTML, CSS, Bootstrap 3, Ajax, and MVC concepts to develop the refreshed design.• Formulate test cases and check if the system is working as per the desired outcome.• Using BitBucket as the version control repository.

Chennai Area, India

• Worked as a part of Data Conversion and Implementation team which dealt with crucial and sensitive data of all the Fidelity's clients in the retirement services business.• Responsible for developing and implementing multiple projects in the Defined Contribution retirement services space (401k plan).• Been part of crucial business level projects and have completed all the tasks with due diligence. A good understanding about the business especially the 401K Plan (based on the US).• Extensively focused on data extraction, transformation (development), analysis, loading and reporting of DC data using Base SAS.• Ensure a smooth conversion process by working closely with the onsite data conversion consultants.• Involved in migration project from SAS on mainframe to SAS on Linux and successfully completed migrating the modules assigned. Worked extensively on the back-end using DB2. Fidelity Research team:• An active contributor to the Fidelity Research team. • Worked on a project related to Stock prediction (of numerous customers) using machine learning. The work majorly focused on Data Wrangling and Data Visualization using Python andTableau.

Chennai, Tamil Nadu

• Trained predominantly on z/OS, COBOL, JCL, CICS and DB2.• Underwent training on Agile, writing, communication and all important aspects for working in a professional environment.• Worked and led a team of 5 for successful completion of a project using COBOL, JCL, CICS, DB2 during the training phase.

Master'S Degree, Information Technology

B.Tech, Computer Science And Engineering