Senior Software Engineer, PsiQuantum

• 5+ years professional software engineering; 3+ years in feedback-control, calibration, robotics, or analogous real-time domains
• Fluency in Python or Julia, particularly in the context of scientific computing, AI/ML, or signal processing
• Fluency in Rust and/or C++17+; comfortable writing lock-free, wait-free, and numerically stable code paths
• Proven track record delivering production systems with real-time or ultra-low-latency requirements
• Hands-on experience interfacing with hardware over PCIe, Ethernet, or custom serial buses; confident reading schematics & timing diagrams
• Working knowledge of Linux internals (irq, cgroups, NUMA, hugepages) and high-performance networking stacks
• Strong foundation in one or more of: quantum information processing, artificial intelligence, robotics, control theory, optimization, signal processing, or experimental physics
• B.S. in CS, EE, Physics, or related discipline (or equivalent practical experience)

Desirable

• The Control Software & OS Core Team at PsiQuantum works closely alongside engineers and scientists in the electronics, system architecture, and validation teams and is responsible for building the scalable, distributed, fault-tolerant control plane and operating system for utility scale photonic quantum computers
• Our team is responsible for orchestration, scheduling, kernel architecture, co-design, calibration, validation, providing abstractions, systems, and operating software for the immense heterogenous fabric of co-processors, networks, and photonics that are critical to the success of our company’s goal of building the world’s first useful quantum computer
• As a Senior Software Engineer, Calibration & Control you will design and implement the next generation of calibration algorithms, controls, and software that keep our quantum processors in spec 24×7x365
• Architect and implement calibration and adaptive control software in Rust (no-std + async), C++20, and Python targeting x86, GPUs, DPUs, and embedded MCUs
• Design closed-loop optimization algorithms (e.g., Bayesian, stochastic gradient descent, ADAM) that maximize system performance and stability under drift and environmental noise
• Integrate with high-speed fabrics: libfabric, RDMA (RoCEv2/GDR), and FPGA PCIe DMA endpoints
• Build scalable simulation/emulation harnesses (Python, Rust, cuQuantum) to de-risk algorithms before system bring-up
• Implement hooks for observability metrics, traces, SLOs and partner with sibling teams to integrate into our observability infrastructure
• Collaborate daily with physics, validation, firmware, and FPGA teams to co-design HW/SW interfaces and define calibration priorities
• Conduct rigorous code reviews, design reviews, and root-cause analyses; uphold our bar for deterministic, safety-critical code

• Please include the word "purple" in the cover letter submitted