Senior Software Engineer, AI for Quantum

Overview

Quantum computing holds the promise of humanity's mastery over the natural world, but only if we can build a

real

quantum computer. PsiQuantum is on a mission to build the first real, useful quantum computers, capable of delivering the world-changing applications that the technology has long promised. We know that means we will need to build a system with roughly 1 million qubits that supports fault tolerant error correction within a scalable architecture, and a data center footprint.

By harnessing the laws of quantum physics, quantum computers can provide exponential performance increases over today's most powerful supercomputers, offering the potential for extraordinary advances across a broad range of industries including climate, energy, healthcare, pharmaceuticals, finance, agriculture, transportation, materials design, and many more.

PsiQuantum has determined the fastest path to delivering a useful quantum computer, years earlier than the rest of the industry. Our architecture is based on silicon photonics which gives us the ability to produce our components at Tier-1 semiconductor fabs such as GlobalFoundries where we leverage high-volume semiconductor manufacturing processes, the same processes that are already producing billions of chips for telecom and consumer electronics applications. We also benefit from the quantum mechanics reality that photons don\'t feel heat or electromagnetic interference, allowing us to take advantage of existing cryogenic cooling systems and industry standard fiber connectivity.

In 2024, PsiQuantum announced two government-funded projects to support the build-out of our first Quantum Data Centers and utility-scale quantum computers in Brisbane, Australia and Chicago, Illinois. Both projects are backed by nations that understand quantum computing's potential impact and the need to scale this technology to unlock that potential. And we won\'t just be building the hardware, but also the fault tolerant quantum applications that will provide industry-transforming results.

Quantum computing is not just an evolution of the decades-old advancement in compute power. It provides the key to mastering our future, not merely discovering it. The potential is enormous, and we have the plan to make it real. Come join us.

There\'s much more work to be done and we are looking for exceptional talent to join us on this extraordinary journey!

Job Summary

PsiQuantum is seeking an experienced Machine Learning (ML) expert to join our AI for Quantum initiative, focused on accelerating progress in Quantum Error Correction (QEC) and related computational research.

This role will partner closely with physicists and software engineers to develop, optimize, and scale ML models supporting quantum error correction and error modelling.

The ideal candidate brings deep expertise in large-scale model training and systems optimization, a solid mathematical or physical sciences foundation, and the ability to integrate advanced ML methods into a broader scientific software stack.

Responsibilities

Develop large-scale pretraining, fine tuning and inference efforts for models used in QEC and related classical control problems.

Design, implement, and optimize GPU / CUDA / C++ kernels and distributed training pipelines for high-performance model development.

Collaborate with physicists and engineers to translate quantum phenomena and simulation outputs into ML-relevant data representations.

Prototype and evaluate new ML architectures for solving QEC-related classical control problems.

Work closely with infrastructure teams to ensure seamless integration of ML components into existing quantum computation pipelines.

Drive best practices in ML experimentation, data curation, and reproducible research within the team.

Experience / Qualifications

8+ years of professional experience with a strong background in mathematics or physics (Bachelor\'s or higher in a quantitative field such as Physics, Applied Math, Computer Science, or related discipline).

Proven expertise in large-scale pretraining, distributed optimization, and scaling methods (e.g., model / data parallelism).

Fluent in Python and at least one systems programming language (C, C++, Rust).

Proficiency in GPU programming and kernels (e.g. CUDA, Triton, Warp, CuTe, CUTLASS).

Experience with GPU programming and performance profiling for ML workloads.

Familiarity with modern ML frameworks such as PyTorch and JAX.

Excellent communication skills and ability to collaborate with cross-disciplinary teams spanning physics, ML, and software engineering.

Knowledge of model compression, distributed systems, or compiler-level optimization for ML runtimes.

Proven ability to work closely with subject matter experts, data analysts, or other non-traditional software stakeholders.

Excellent communication, problemsolving, and crossteam collaboration skills.

Preference for those with prior exposure to quantum computing concepts or physics-informed ML.

PsiQuantum provides equal employment opportunity for all applicants and employees. PsiQuantum does not unlawfully discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, or any other basis protected by applicable laws.

Note : PsiQuantum will only reach out to you using an official PsiQuantum email address and will never ask you for bank account information as part of the interview process. Please report any suspicious activity to recruiting@psiquantum.com.

We are not accepting unsolicited resumes from employment agencies.

The ranges below reflect the target ranges for a new hire base salary.

One is for the Bay Area (within 50 miles of HQ, Palo Alto), the second one (if applicable) is for elsewhere in the US (beyond 50 miles of HQ, Palo Alto). If there is only one range, it is for the specific location of where the position will be located. Actual compensation may vary outside of these ranges and is dependent on various factors including but not limited to a candidate\'s qualifications including relevant education and training, competencies, experience, geographic location, and business needs. Base pay is only one part of the total compensation package. Full time roles are eligible for equity and benefits. Base pay is subject to change and may be modified in the future.

U.S. Base Pay Range

$170,000 — $200,000 USD

Bay Area Pay Range

$205,000 — $220,000 USD

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