Role Overview

We are seeking a Senior Quantum Machine Learning Scientist to serve as a technical leader at the intersection of quantum computing, machine learning, and applied mathematics. This role is for a scientist who does not merely implement models, but shapes the intellectual direction of the company, defining what should be built, how it should be built, and when a given approach is fundamentally sound or flawed.

The Senior QML Scientist will conduct groundbreaking research in quantum machine learning, design and evaluate state-of-the-art quantum and hybrid quantum-classical models and translate theoretical advances into implementable architectures suitable for near-term and future quantum hardware. They will play a central role in identifying novel algorithmic directions, stress-testing assumptions, and ensuring that our models are principled, scalable, and defensible from both a scientific and commercial standpoint.

This position carries significant influence. The ideal candidate is a trusted internal authority, someone whose judgment helps the company avoid dead ends, recognize genuine breakthroughs, and maintain a high standard of scientific rigor.

Key Responsibilities

Research Leadership

• Lead original research in quantum machine learning, quantum algorithms, and hybrid quantum-classical methods.
• Identify promising new directions and assess their theoretical and practical viability.
• Maintain awareness of the cutting edge in QML, including both academic and industrial developments.

Model Design & Evaluation

• Design novel QML architectures (e.g., variational models, quantum transformers, quantum reservoirs, graph-based methods).• Critically evaluate existing and proposed models, providing clear guidance on strengths, limitations, and failure modes.
• Establish best practices for model design, benchmarking, and validation.

Implementation & Prototyping

• Implement and prototype quantum and hybrid models using modern quantum software stacks.
• Translate abstract algorithms into executable workflows compatible with NISQ-era constraints.
• Work closely with engineering teams to ensure theoretical intent is preserved in implementation.

Strategic Technical Guidance

• Act as a senior technical voice in product and research decisions.
• Provide candid, constructive feedback, calling out when an approach is correct, promising, or fundamentally misguided.
• Help align research goals with long-term company strategy and near-term deliverables.