Experience

• 

  Ellipsonic

  Oct 2016 - Sept 2017

  Iot intern

  Worked on multiple IoT Arduino based projects - 1. Automatic sensor-based water sprinkler 2. Collecting data from the heart-rate sensor and sending data to ThingsSpeak Cloud3. Building custom-designed front-end to graphically show the different metrics collected from the sensors

• 

  Just practicals!

  Jul 2017 - Aug 2017

  Entrepreneur internship

  Mini Incubation Program - 1. The idea to Product Prototype (Early-stage product development)2. Product Prototype to its Commercial Launch & Funding Support3. Dedicated Mentorship from Industry Experts.4. Access to world-class Research Lab.5. Access to technical experts to discuss our ideas6. Market Linkages and understanding the power of digital marketing7. Funding platform

• 

  Leanovate

  Sept 2017 - Jun 2020

  1. Developed front-end for applications using React.js2. Developed adapter to transfer large amounts of data between two entities3. Developed Google calendar plugin for a booking application4. Developed Alexa for Tridium Niagara 4 platform5. Developed a GPS adapter in Tridium Niagara 4 platform parsing NMEA sentences from selective satellites integrated with Firebase and Google Maps6. Developed a complete Hot-Desking hybrid application using at the time latest frameworks present and integrated with Access Control System(HID ACS) that works with the BMS system for seamless employee experience.7. Implemented and Designed workflow of an agent-less IT Automated system for AWS using Red-Hat's tool called Ansible to invoke new EC2 instances for each customer deployment on the successful pass rate of test cases at the end of each build (Jenkins) which also then installs all requirements and sets up a Kubernetes cluster once the EC2 instances are up and running.8. Developed a POC for Tridium BMS system where the data is sent from the source using HTTP protocol in JSON format and our module converts this data to MODBUS SERIAL RTU format, sends this data over a USB to MODBUS 2-wire converter which is then received at the destination which is a MODBUS Serial driver (JACE - BMS SYSTEM). Show less 1. Innovated the integration of Tridium Niagara platform with Jenkins(CI&CD) such that it handlesversioning of the module compiles the code and provides a report (HTML, PDF) on the static analysis of the code.2. Composed a complete HVAC simulation kit using micro-controllers integrated with the BMSsystem(Tridium-JACE)3. Developed a web-based application for Data Center Infrastructure Management integrated with the Tridium Niagara platform (BMS).4. Handled the company’s online presence – regularly updated the company’s website.5. Participated in ongoing marketing campaigns and exhibitions.6. Prepared presentations for prospective clients. Show less

  • Full-stack Developer & IoT/IIoT Developer

    Jun 2018 - Jun 2020

  • Full-stack Developer & Microcontroller/Microprocessor Intern

    Sept 2017 - May 2018
• 

  Baudrate.io

  Jul 2020 - Feb 2022

  Tridium niagara software developer

  Software Developer at Baudrate.io working on developing solutions in the field of IoT using the open Niagara framework.Projects Worked on -1. Upgrading custom-tailored reporting tool2. Upgrading and Redesigning existing Alexa solution3. Developed NDriver to implement SOAP protocol using the Niagara framework to import, read and write to sensor points.4. Developed JS part of widget application that supports 46 different chart types in N4 including 3D charts, used Bajascript, RPC, servlet, java, and vanilla javascript extensively to achieve this.5. Tested the OCPP protocol with various electric car charging station vendors during the plugfest6. Developed log parser to extract certain parameters from large amounts of logs. Show less

• 

  Citiustech

  Mar 2022 - Aug 2024

  1. Designing AI solutions : Responsible for designing AI solutions that meet the client’s requirements.2. Leading a team: Responsible for leading a team of developers and data scientists to deliver high-quality solutions on time and within budget. This would involve managing the team’s workload, providing guidance and support, and ensuring that the team is working effectively together.3. Implementing solutions: Responsible for implementing the AI solutions that I/we have designed. This would involve writing code, configuring systems, and integrating different components of the solution.4. Testing and debugging: Responsible for testing and debugging the AI solutions that I/we have implemented. This would involve identifying and fixing any issues that arise during testing.5. Documentation: Responsible for documenting the AI solutions that I/we have designed and implemented. This would involve creating technical documentation, user manuals, and other materials that help users understand how to use the solution.6. Staying up-to-date: Responsible for staying up-to-date with the latest developments in AI and machine learning. This would involve attending conferences, reading research papers, and experimenting with new technologies. Show less 1.Develop, deploy, and manage machine learning models and workflows in production environments.2.Build and manage model deployment infrastructure, and testing and validation frameworks.3.Collaborate with data scientists and software engineers to develop and deploy machine learning solutions.4.Implement best practices for security, compliance, and cloud-based infrastructure.5.Monitor model accuracy, performance, and uptime.6.Ensure that cloud-based machine learning workflows are compliant with relevant regulations and security requirements.7.Manage cloud-based machine learning workflows across multiple environments, including development, staging, and production environments.8.Cloud computing platforms (AWS SageMaker , GCP Vertex AI)9.Machine learning frameworks (TensorFlow, scikit-learn) Show less

  • Technical Lead - 1 (AI Solutions Architect & AI/MLOps Engineer)

    Oct 2023 - Aug 2024

  • Senior Software Engineer (AI Engineer)

    Mar 2022 - Sept 2023
• 

  Clio - cloud-based legal technology

  Aug 2024 - now

  Intermediate mlops engineer

  1.Model Deployment: Collaborating with data scientists to deploy machine learning models into production using best practices in CI/CD.2.Infrastructure Management: Managing and optimizing cloud infrastructure to support scalable and efficient ML workflows.3.Monitoring and Maintenance: Implementing monitoring solutions to track model performance and ensure reliability, making necessary adjustments as required.4.Collaboration: Working closely with cross-functional teams, including software engineers and product managers, to integrate ML solutions into Clio’s product offerings.5.Documentation and Best Practices: Creating comprehensive documentation and establishing best practices for model development and deployment. Show less