~experience
A brief timeline of where I've worked and what I have built.
Software Engineer - I
- Took ownership of high-impact modules such as Health Assessment, Delivery Analytics, and Cybersecurity Reports, delivering within tight timelines and minimal defects.
- Developed scalable backend systems in Python (Django, GraphQL) and PostgreSQL — implemented multiple models, APIs, and admin tools that automated reporting workflows and reduced manual interventions.
- Enhanced system automation by optimizing cron jobs for performance metrics computation, integrating APIs for realtime data updates and analytics.
- Contributed to full-stack development by implementing dashboards and UI updates using React and Ant Design, and improving test coverage to over 80%.
- Conducted 100+ code reviews, resolved 100+ quality issues, and supported multiple production releases ensuring stable deployments and reliable integrations.
- Mentored new joiners, guided peers in API design and debugging, and collaborated closely with QA and product teams to validate complex workflows.
- Spot Award for delivering high impact feature in tight deadline.
- Created features for performing analytics on team's risks and performances.
- Designing and developing features for org-wide analytics generation.
→ Python, Django, GraphQL, PostgreSQL, React, Ant Design, APIs, Automation, Testing
Software Engineer Intern
- Developed 20+ REST APIs in Python (FastAPI) for an Android app to track carbon footprint, enabling data-driven sustainability insights.
- Built features like ride-pooling and facility management, integrating PostgreSQL and Power BI dashboards for generating analytics.
- Created document query and graph-generation chatbots using Generative AI and RAG techniques.
- Worked with FastAPI, Java Spring Boot, Angular, Kafka, Airflow, and cloud-based data pipelines.
- Worked on creating a sustainability android application for tracking the carbon footprint.
- Runner Up of the 'HashedIn Product Month'.
→ Python, FastAPI, Java Spring Boot, Angular, Kafka, Airflow, PostgreSQL, Power BI, Generative AI, RAG
Software Engineer Intern
- Built an Android prototype for image Super Resolution on edge devices with low network latency.
- Trained a cascading residual CNN on 10,000 images, improving inference time from 17s to 9s.
- Worked with PyTorch, TensorFlow, and Python for model training and optimization.
- Worked on creating an android application and deploying a deep learning model on a resource-constrained device.
- Trained a GAN model over 10k high resolution images and created checkpoints over 26k iterations.
- Performed literature survey and trade off analysis between various deep learning models.
- Increased output quality and reduced inference time by leveraging the knowledge from literature study and model training.
- Delivered knowledge exchange sessions on GANs to different teams at Microsoft.
- Engaged with various teams to gather the use case of the application to solve their internal issues.
→ Python, PyTorch, TensorFlow, Android, Deep Learning, GANs, CNN, Edge Devices
