Intrinsic is unlocking the creative and economic potential of industrial robotics for millions more businesses, entrepreneurs, and developers.

Engineered full-stack Perception solutions for the Intrinsic Flowstate platform, spanning from frontend camera views and WebRTC transport to backend camera services and device drivers.

Systematically optimized the perception stack, successfully improving data throughput and reducing latency across the system.

Intrinsic joined Google in February, 2026. More information can be found at https://www.intrinsic.ai/blog/posts/intrinsic-joins-google-to-accelerate-physical-ai.

Staff Engineer at Akasha: 03/01/2021 - 05/15/2022

Developed various components of Akasha's vision platform as a member of the Systems team, including the GUI and shared memory transfer of high bandwidth data. Additionally, supported the Algorithms team with infrastructure and tooling support.

In 2021, Akasha was operating as an independent subsidiary of Vicarious. Vicarious was acquired by Intrinsic in May, 2022. More information about the acquisition can be found at https://www.intrinsic.ai/blog/posts/new-chapter-for-intrinsic/.

Motus Data is an automation startup specializing in Oil and Gas technologies. They aim to provide cloud visualization and monitoring tools for the safety and maintenance of remote sites.

• Designed and built an IoT system which aggregates, processes, and uploads sensor data.

• Worked closely with data scientists and electrical engineers to validate and test the data flow.

Focal Systems is a deep learning and computer vision company solving some of the biggest problems in retail. Founded by Stanford alumni and part of YC’s winter 2016 batch, the company has since grown considerably and developed products to tackle continuous out-of-stock detection and scalable automated checkout.

• Joined as one of the first engineers and helped build the company from the ground up.

• Architected, built, and deployed a user experience platform to hundreds of IoT devices used by thousands of customers every day in major retail chains. The system was designed to run Deep Learning models with a small memory footprint on device.

• Deployed an IoT platform for data acquisition in retail environments, which captured millions of images across clients’ stores and converted them into real-time, actionable insights to improve shoppers' experiences, reduce operating costs, and drive sales.

• Led a multidisciplinary team to research and develop checkout automation for retail. Planned the project development and deployment, and designed the system architecture.