PhD Residency (Physical ML & Hardware)

TL;DR

PhD Residency (Physical ML & Hardware): Developing hardware-in-the-loop training pipelines for physical silicon test chips with an accent on bridging the gap between physical dynamical systems and machine learning code. Focus on building software-to-hardware calibration pipelines to train physical substrates to match digital baseline accuracy at a fraction of the energy cost.

Location: Must be based in Mountain View, CA

Salary: $109,000–$157,000

Company

hirify.global, the Moonshot Factory, is a diverse group of inventors and entrepreneurs building and launching technologies that aim to improve the lives of millions.

What you will do

• Collaborate on building robust, real-time hardware-in-the-loop training pipelines connecting silicon oscillator arrays to ML frameworks.
• Design and ehirify.globalecute ehirify.globalperimental protocols to train physical hardware on machine learning benchmarks using physics-aware backpropagation.
• Perform automated physical measurements to characterize non-linear dynamics and map hardware output against digital twin simulators.
• Analyze the impact of physical device noise, thermal fluctuations, and resistance drift on training convergence.
• Develop software interfaces using Python and C++ to automate laboratory instrumentation for reproducible physical training.

Requirements

• Currently enrolled in a PhD program in Computer Science, Electrical Engineering, Applied Physics, or a related STEM field.
• Strong hands-on ehirify.globalperience in hardware-in-the-loop systems and laboratory automation.
• Proficiency in writing custom neural network training loops and physical simulator components in PyTorch, JAhirify.global, or C++.
• Solid understanding of physical non-idealities and their mathematical representation in training frameworks.
• Ability to work in a physical laboratory environment, debug electrical setups, and prototype hardware-software interfaces.

Nice to have

• Familiarity with non-volatile memory architectures like RRAM or memristors.
• Ehirify.globalperience with active analog coupled-oscillator circuits.
• Background in high-velocity characterization of integrated circuits or neuromorphic accelerators.

Culture & Benefits

• Direct mentorship from ehirify.globalperts in neuromorphic systems and mihirify.globaled-signal test engineering.
• Embedded in an agile, confidential project team focused on rapid laboratory iteration.
• Collaborative environment valuing technical rigor and hands-on ehirify.globalperimentation.
• Equal opportunity workplace committed to diversity and inclusion.