Oct 2025 – Present · 7 mos · San Francisco Bay Area

• Steadwing is an autonomous on-call engineer that diagnoses root cause in under 5 mins and fixes it. It correlates evidence across your entire stack (logs, metrics, traces, and code) and delivers actionable RCAs with real remediation: PRs, rollbacks, config changes and more. Ask follow-up questions about incidents and general questions about your infrastructure. Connect any of the 20+ most widely used integrations in seconds.

Aug 2025 – Oct 2025 · 2 mos · Gujarat, India · On-site

• Onboarded 25k+ really good engineers in < 1.5 months because of the unique data collection flow.
• Had more than 100k+ unique visitors.

Jul 2024 – Jul 2025 · 1 yr · Remote

• Lead maintainer of the Mem0 repo (45k stars, 14M+ downloads).
• Primarily handled the backend and Infra on AWS (serving latency-heavy 5k req/s).
• Co-authored a research paper published at ECAI (a top AI conference) with 350+ citations.
• Co-developed OpenMemory Cloud (MCP), a platform to manage memories across AI tools like Claude, Cursor, and Windsurf.
• Made integrations to Microsoft, BrowserUse, Raycast, CrewAI etc.
• Interacted with customers, handled their requests and calls and built multiple demo projects to showcase the product.

Apr 2023 – Jul 2024 · 1 yr 3 mos

• Integrated RAG for multiple languages and file formats(PDFs, CSVs, and excel). It's used for question answering from documents, analyzing data, and creating user-specific plots. Here we also extract tables and images to provide more information. Also working around large language models like GPT-4 and Claude 3 to add better capabilities.
• Added new Inverse Prediction flow. This led to more accurate results for material properties prediction based on a set of ingredients.
• Guided 2 interns throughout their time here and also helped in automating CI/CD and database workflow.

Nov 2022 – Apr 2023 · 5 mos

• Integrated Explainable AI for regression and classification models. Presenting multiple charts to understand predictions made by models. Deployed it on AWS Fargate for scalability.
• Reduced response time for a Machine Learning API by 20%.
• Worked on integrating classification models for imbalanced datasets and Data Sanity checks.

Sep 2022 – Aug 2023 · 11 mos

• I taught my peers and juniors on how to use Tensorflow and Keras to build deep learning-based applications. Also guided them on building end-to-end projects using these frameworks.
• Hosted four challenges in building apps around Computer Vision and NLP.

Jul 2022 – Oct 2022 · 3 mos

• Developed a custom Object Detection + OCR model for reading Digital Odometer. The mAP for the detection model was 96%.
• Worked on Instance Segmentation and Object Detection using Pytorch. Goal here was to detect the dents, scratches, scrapes, cracks in windshield etc. present on cars and estimate the repairing cost.
• Integrated MLflow for model tracking and Data pipeline for Classification tasks. The classification model was trained for determining the different properties of the car. It included 30+ classes.
• Worked on Detection Transformer(DeTR) for instance segmentation. Also worked on Video Analytics for getting useful insights from video.

Apr 2022 – Jul 2022 · 3 mos

• Mainly worked on Computer Vision projects using Tensorflow. It included Object Detection, background removal and knowing the color and brightness of an image.
• Contributed to ongoing projects using YOLO for Object Detection and OpenCV for tracking and counting objects. This was used in manufacturing industries for counting bottles, towels and boxes. And mAP achieved here was 97.5%. During the Inference test video ran at around 50 FPS.
• Got hands-on experience in annotating real-world industry data using LabelMe and LabelImg for the custom detection models.
• Deployed 2 POCs using Streamlit and Flask. One project was to detect defects in fabrics and calculate the area covered by them. Another project was extracting tables from bills or receipts using OCR. Pytesseract was used for OCR.

Jan 2022 – Mar 2022 · 2 mos · Gujarat, India · Hybrid

• Here I helped teams to build the ML projects for the hackathon. Projects were around Object detection, Pose Estimation, and predictive analysis.
• One of the teams I assisted made it to the finals. They created a project that helps people who can't speak by detecting signs and translating them into language.

Nov 2021 – Dec 2021 · 1 mo · Remote

• Worked on a framework named SpiceAI for building a predicting tweet likes based on the past history of the user.
• SpiceAI used Reinforcement Learning to make predictions on given time-series data.

Apr 2021 – Jul 2021 · 3 mos · Remote

• First I learned about analyzing satellite images using OpenCV and Pillow.
• Built a custom CNN model to detect lakes and rivers from satellite images and then used the company’s prebuilt system to identify its location.
• Worked on setting up a pipeline for collecting and cleaning aerial & satellites data.