Job Description
Join Nexus Labs at the forefront of technological evolution as we pioneer quantum-AI convergence solutions for 2026 and beyond. We're seeking a visionary Quantum AI Research Engineer to develop groundbreaking algorithms that bridge quantum computing and artificial intelligence. This role offers unparalleled opportunity to shape next-gen computational paradigms while collaborating with Nobel-caliber researchers in our state-of-the-art San Francisco facility.
Our ideal candidate thrives at the intersection of theoretical physics and machine learning, pushing boundaries in quantum neural networks and error-corrected AI systems. You'll contribute to projects with direct commercial applications in drug discovery, climate modeling, and autonomous systems – all while enjoying comprehensive benefits including equity, unlimited learning stipends, and flexible work arrangements.
Responsibilities
- Design and implement quantum machine learning algorithms for NISQ-era hardware
- Develop hybrid quantum-classical neural network architectures
- Lead research into quantum error correction for deep learning systems
- Collaborate with hardware teams to optimize quantum-AI co-design protocols
- Publish breakthrough research in peer-reviewed journals and conferences
- Translate theoretical models into scalable commercial prototypes
- Mentor junior researchers in quantum computing best practices
Qualifications
- PhD in Quantum Computing, Physics, or Machine Learning (or equivalent experience)
- Proficiency in quantum programming frameworks (Qiskit, Cirq, PennyLane)
- Strong publication record in quantum machine learning or related fields
- Expertise in Python, TensorFlow/PyTorch, and high-performance computing
- Deep understanding of quantum algorithms (VQE, QAOA, Grover's search)
- Experience with cloud quantum computing platforms (IBM Quantum, Amazon Braket)
- Demonstrated ability to translate complex theoretical concepts into practical solutions