Senior Quantum Control Systems Engineer

Atom Computing; Boulder (CO); On-site; USD 165,000 - 200,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

Unlimited PTO

401K company matching

Disability and life insurance

Job summary

Atom Computing is hiring a senior software/firmware engineer in Boulder to build embedded code powering quantum hardware and high-speed control pipelines. You will design drivers, Linux modules, and real-time systems to meet demanding determinism and throughput requirements.

Ideal candidates have 8+ years of postgrad experience, a CS/EE degree, and proficiency in C++, Python, Rust, or Go with CUDA experience. Collaboration across theory, hardware, and platform teams is essential.

Qualifications

• Bachelor’s degree in Computer Science, Electrical Engineering, or related field.
• At least 8 years of relevant postgraduate professional experience.
• Proficiency in C++, Python, Rust, or Go; CUDA toolchains experience.

Responsibilities

• Build and test embedded firmware and software powering high-speed SDRs and instrumentation.
• Design low-latency software for quantum hardware, including device drivers and kernel modules.
• Evaluate real-time strategies across Linux/RTOS; optimize determinism and throughput.
• Develop orchestration layers for GPUs, FPGAs, and custom electronics for high-bandwidth quantum control.
• Prototype using Rust, Python, C/C++, and CUDA.
• Collaborate with theorists and engineers to translate quantum control into production-ready code.

Skills

C++

Python

Rust

Go

CUDA

Education

Bachelor’s degree in CS/EE

Advanced degree a plus

Job description

Atom Computing is hiring a senior software/firmware engineer in Boulder to build embedded code powering quantum hardware and high-speed control pipelines. You will design drivers, Linux modules, and real-time systems to meet demanding determinism and throughput requirements.

Ideal candidates have 8+ years of postgrad experience, a CS/EE degree, and proficiency in C++, Python, Rust, or Go with CUDA experience. Collaboration across theory, hardware, and platform teams is essential.