Hardware Platform Software Engineer
AI Summary
Builds a hardware abstraction layer and experiment framework that translate AI framework calls into concrete operations on physical hardware, enabling model execution, measurement, and diagnostics across hardware generations.
About this role
About Us
Great Sky is a technology startup based with a mission to rebuild AI from first principles. We are pursuing neuroscience-inspired hardware and algorithms that overcome the greatest challenges in scaling AI systems.
The Role
We are looking for a Hardware Platform Software Engineer to extend the software platform through which our hardware is operated. Two needs converge here: a hardware abstraction layer (HAL) that translates abstract, model-level behaviors into concrete operations on real analog hardware, and an experiment framework that lets our scientists and engineers define and execute measurements on our chips with minimal overhead. If you have owned substantial parts of the hardware-facing software stack for quantum computers, analog accelerators, photonic processors, or large scientific systems, you are likely a good fit for the expectations of this role.
Key Responsibilities
Build an enhanced hardware abstraction layer (HAL): the software layer which translates calls from the AI framework to driver level calls to our physical hardware. This layer enables execution of models, capability discovery, versioning across hardware generations, and parameter translation to a physical mapping on hardware.
Build a robust experiment framework, so measurement routines are both easy to use and elegantly declared.
Provide the analysis pipelines, capturing maximum value from every inference and measurement.
Present a unified API for both simulated and physical backends. Interfacing this API to our existing simulation framework for verification and parity testing.
Define and maintain the middleware between the driver layer and the AI frameworks. Introducing telemetry, diagnostics, and regression testing that keep the platform trustworthy across hardware revisions.
What Success Looks Like in the First Year
A v1 HAL is in production use: our AI frameworks execute models on real hardware exclusively through your interface
Clear, documented contracts exist at both boundaries of the layer, validated by automated tests.
Our engineers leverage your framework for efficient design and execution of key measurement routines.
Qualifications
Required:
Bachelor's or Master's degree in Computer Science, Electrical Engineering, Physics, or a related field (or equivalent experience),
5+ years of professional software engineering for control of real physical hardware (e.g., quantum control stacks, novel accelerators, photonic systems, scientific instrumentation, embedded systems, or comparable platforms).
Demonstrated ownership of an API or abstraction layer that other engineers used: you have designed interfaces, defended their boundaries, and evolved them
Superior proficiency in Python and working proficiency in at least one systems language (e.g., C, C++, or Rust).
Hands-on experience orchestrating lab instrumentation in software (e.g., SCPI instruments, DAQs, AWGs, cameras, motion stages, or cryogenic systems)
Strong testing instincts: unit, integration, and regression testing, hardware-in-the-loop test design, and simulation/hardware parity testing.
Excellent technical writing and communication: high-quality architecture and interface documentation, and the ability to negotiate contracts across disciplines.
Preferred:
Experience with runtime or compiler-adjacent layers for novel accelerators.
Familiarity with superconducting electronics, photonics, or cryogenic systems.
Experience with streaming or high-throughput data systems (video, RF, DAQ)
Familiarity with neural networks and ML frameworks such as PyTorch or JAX
Growth Opportunities
You will begin as the sole owner of this software layer: a rare degree of technical ownership over critical infrastructure. As our hardware scales to large multi-chip systems and our platform matures toward production workloads, the scope and sophistication of this layer will grow substantially. The ideal candidate will grow with it: defining the platform software roadmap, setting engineering standards, mentoring other engineers, and building and leading a dedicated platform software team.
Benefits and Perks
Meaningful equity ownership in an early-stage deep tech company
Employer-matched 401(k)
Health, dental, vision, and life insurance
Flexible PTO
Support for ongoing learning, conference attendance, and skill development
Our culture is onsite by default (we're founded by scientists who are used to working in the lab), with flexibility for hybrid arrangements. For the right person and role, we're open to filling roles remotely
Skills
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