Summary
Shreeyam Kacker is an Edge Compute Machine Learning Engineer based in San Francisco with a decade of hands-on experience applying AI, computer vision, and embedded systems to space and aerial applications. He blends deep academic credentials—a PhD in Aeronautics & Astronautics with a minor in AI/Computer Vision and an MS with top marks from MIT—with industry work building production edge ML at Planet and prototyping optical wireless communications at X. His research at MIT STAR Lab led a NASA-funded hemispherical pointing and tracking project (MOSAIC) using liquid lenses, demonstrating an ability to turn novel hardware concepts into funded, testable systems. Equally comfortable in firmware, avionics and machine learning stacks, he has a track record of designing robust DAQ, telemetry and control systems that have flown to near-space. Known for bridging rigorous research and pragmatic engineering, he brings systems-level thinking to deployable edge ML in challenging physical environments.
10 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Aeronautics and Astronautics, minor in AI and Computer Vision, Doctor of Philosophy - PhD, Aeronautics and Astronautics, minor in AI and Computer Vision at Massachusetts Institute of Technology
Master of Engineering (MEng), Aeronautical Engineering, First Class Honours, Master of Engineering (MEng), Aeronautical Engineering, First Class Honours at Imperial College London
A-levels, A-levels at Bancroft's School
Hindi, English, Korean