Hardware Platform Software Engineer

Great Sky, Inc.; Boulder (CO); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Equity stake

401(k) match

Health, dental, vision, life

Flexible PTO

Learning support

Job summary

Great Sky, Inc. is seeking a Hardware Platform Software Engineer to extend the software platform that operates our hardware. You will own the HAL translating model calls to driver-level operations and build an experiment framework to run measurements on our chips with minimal overhead.

You will collaborate with AI and hardware teams to define contracts, enable simulated and real backends, and introduce telemetry, diagnostics, and regression testing to keep the platform stable across revisions.

Qualifications

• Bachelor's or Master's in CS/EE/Physics or related field or equivalent experience.
• 5+ years software engineering for control of real hardware required.
• Ownership of an API or abstraction layer design and evolution.

Responsibilities

• Build the HAL translating AI framework calls to driver-level hardware commands.
• Create a robust experiment framework for easy, declarative measurements.
• Provide analysis pipelines to maximize value from inferences and measurements.
• Define a unified API for simulated and physical backends with verification.
• Maintain middleware between driver layer and AI frameworks with telemetry.

Skills

Python

API design

System programming

Lab instrumentation

Testing

Technical writing

Education

Bachelor's or Master's in CS/EE/Physics or related field

Tools

SCPI

DAQ

AWG

Cameras

Cryogenic systems

Job description

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