1. Worked on a platform where I helped roll out over 200 cutting-edge computer vision models (like YOLO, PyTorch, Transformers, and more). It’s a no-code tool, so even non-coders can easily create and deploy AI vision applications.2. Built a full workflow from scratch — everything from data processing and annotations to training and deployment for tasks like image classification, detection, and segmentation.3. Created a smart scheduling service that figures out what tasks to prioritize based on user needs and system capacity. It keeps everything running smoothly!4. Tweaked machine learning pipelines to make them faster and more efficient, boosting processing speeds by 25% and speeding up model launches.5. Designed a super flexible data pipeline that supports all sorts of formats (MS COCO, Pascal VOC, ImageNet, etc.), making it easy to train and deploy models for both images and videos.6. Automated deployment processes to set up hardware (GPUs, CPUs) and fine-tuned for better inference speeds, cutting deployment time almost in half.7. Simplified dataset prep workflows, slashing processing time by 60%, which means faster and more efficient model development.

1. Took charge of projects worth over $120K, leading a team of 20 and making sure everything got delivered on time.2. Worked with my senior manager to wrap up a $50K project successfully and landed a $1M deal with the same client.3. Kept things running efficiently, hitting a gross margin of over 75%.4. Acted as the go-to person for client communication, making sure we were always on the same page.5. Spotted and tackled risks early, saving us $20K–$40K and avoiding delays of 4–5 weeks.6. Managed client change orders smartly, pulling in $30K–$50K in extra profit.7. Streamlined workflows by rolling out Agile and Scrum practices and using tools like JIRA and CI/CD platforms.

Agile Development and Waterfall model development. Continuous Integration and Delivery by means of Subversion.Collaborated with clients like HDFC Bank, Canara Bank and implemented containerization of Oracle Flexcube Retail Banking on Kubernetes, Docker. Development of various screens (Full stack) on the Flexcube software update. Designed and Developed various Grafana Dashboards for systematic monitoring of various live deployments, system monitoring, Bank transactions including NEFT, RTGS, IMPS, uploads and extracts with the functionality of identification of potential issues which led to a significant reduction in system downtime. Creation of interactive visualizations via Kibana to enable data driven decision making. Automated complex deployments via shell scripting, python and Jenkins. Implemented system Hooks and automated periodic backup of all system files. Use of metrics like Cadvisor, Kube-state metrics (KSM) and node exporter from Prometheus to visualize performance and configure important alerts.Started Ansible Integration to manage large systems together, improve efficiency for application deployment, configuration managements and updates.

1. JavaScript; React Engineer, Established CI/CD workflows with GitHub for version control in an Agile framework2. Managed the migration from Heroku to AWS, reducing operational costs by 45% and optimizing infrastructure.3. Integrated Amazon SES and S3 Bucket services for enhanced email delivery and storage capabilities, implementing a secure IAM architecture.4. Developed middleware solutions for improved system reliability, reducing response times by 45% using MERN stack and RESTful APIs.5. Created API Calls for data access and management, database enhancement, and UX improvements by implementing search functionality using MongoDB Atlas Search.