Mike Lambeta
AI Research Engineer, Hardware at Meta
Menlo Park, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMike Lambeta is an AI research engineer focused on hardware with 14 years of experience building systems that bridge embedded design, infrastructure, and machine learning at scale. Based in Menlo Park, he currently drives hardware research at Meta after prior roles in infrastructure research and medical device hardware design, bringing a pragmatic mix of circuit-level know-how and systems thinking. His open-source work includes full-stack contributions to a time-synchronization reference model that spans firmware, backend services, and documentation, reflecting a comfort with both low-level timing hardware and web-facing tools. Known for turning prototyping work into operational solutions, he combines rigorous R&D practices with hands-on implementation across hardware, firmware, and distributed systems.
14 years of coding experience
2 years of employment as a software developer
University of Manitoba
English, Croatian
Github Skills (6)
python10
hardware9
website-development9
javascript9
synchronization8
distributed-systems7
Programming languages (2)
Github contributions (5)
Time-Appliances-Project/Time-Card
Aug 2021 - Sep 2022
Develop an end-to-end hypothetical reference model, network architectures, precision time tools, performance objectives and the methods to distribute, operate, monitor time synchronization within data center and much more...
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:15 commits, 22 pushes, 1 branch in 1 year 1 month
Contributions summary:Mike contributed to both the frontend (website) and backend (timecard/MAC) aspects of the project. They added a new timetickler application for changing MAC parameters, indicating backend development. Furthermore, they committed changes related to website documentation and configuration, indicating frontend or full-stack work. Additionally, the hardware commits suggest the user may work on hardware.
monitorsdnload-balancinglinearizabilitymonitoring
facebookresearch/PyTouch
May 2021 - Sep 2022
PyTouch is a machine learning library for tactile touch sensing.
Contributions:22 commits, 22 PRs, 32 pushes in 1 year 4 months
tactilesensingtouchmachine-learningmachine-learning-library
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