About the role
We're hiring a Quantum AI Engineer to play a pivotal role in designing and deploying machine learning models that integrate with our globally unique quantum processors. Based out of our office at UNSW Sydney, you'll sit within the Software Engineering team and collaborate closely with quantum engineers, hardware specialists, and customer organisations to build high-impact ML pipelines on our Watermelon quantum devices.
This role is ideal for someone who thrives at the intersection of cutting-edge AI and quantum technology. You'll help shape real-world applications across finance, energy, telco, defence and beyond—working with internal and external ML experts to deliver tailored, outcome-driven solutions that push the boundaries of what's possible.
Role responsibilities
Design, develop, and deploy machine learning models that integrate with SQC's quantum systems.
Collaborate with internal quantum engineering teams and external customers to define use-cases and deliver fit-for-purpose ML solutions.
Translate business requirements into technical problem statements and model architectures.
Build and optimise ML pipelines for classification, inference, and decisioning tasks.
Advise customer ML teams on model selection, tuning, and integration with quantum-enhanced workflows.
Work closely with quantum physicists and software engineers to realise result-driven AI/ML pipelines on multi-qubit quantum devices.
Evaluate and recommend tools, frameworks, and techniques to improve model performance and scalability.
Stay abreast of emerging trends in machine learning, quantum computing, and applied mathematics.
Contribute to a safe and inclusive working workplace, identifying and managing risks in your area of responsibility.
Your experience
Bachelor's, Master's, or PhD in Computer Science, Engineering, Mathematics, or a related field.
Proven track record in developing and deploying ML models with measurable business impact.
Deep understanding of ML paradigms, architectures, and optimisation techniques.
Strong mathematical foundation, with exposure to quantum computing or quantum mechanics (academic or practical).
Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
Experience with cloud platforms (AWS, Azure, or Google Cloud) and big data technologies.
Familiarity with data engineering practices and pipeline development.
Ability to define clear problem statements and select appropriate modelling approaches.
Strong communication skills and ability to collaborate across technical and non-technical teams.
The recruitment process
For roles at SQC, expect 3-4 interviews, meeting a few members of the team and focusing on your core eligibility for the role, your skills and how they align, and finally your values and how they align. We'll give you a more specific runthrough if you're successful in making it to the first interview.
As part of our obligations to our customers, we require that successful candidates submit to background checks, including a National Police Check, Right to Work checks, as well as employment and qualifications verification. We won't contact anyone until we're confident there's a fit between SQC and yourself.
How to apply
The best and simplest way is to apply directly here, rather than messaging anyone on the SQC team directly. If you have any questions that you'd like answered before committing to applying, please feel free to email us at
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📌 Quantum Ai Engineer
🏢 Silicon Quantum Computing
📍 Sydney