Job Description
Join Nexus Dynamics Inc. at the forefront of technological evolution as we pioneer quantum-ML hybrid systems for 2026's most critical challenges. Our interdisciplinary team redefines computational boundaries by merging quantum algorithms with neural networks. You'll architect breakthrough solutions for drug discovery, climate modeling, and financial optimization while working in our state-of-the-art San Francisco lab. This role offers unparalleled growth opportunities in quantum computing's most promising frontier.
Responsibilities
- Design and implement quantum machine learning algorithms for real-world applications
- Optimize quantum-classical hybrid models using GPU/TPU acceleration frameworks
- Collaborate with physicists to translate quantum phenomena into ML architectures
- Lead cross-functional teams in deploying quantum-ML pipelines
- Publish research in top-tier quantum computing conferences
- Develop error-correction protocols for quantum neural networks
Qualifications
- PhD in Computer Science, Physics, or Mathematics with quantum focus
- 3+ years implementing ML algorithms (TensorFlow/PyTorch proficiency)
- Experience with quantum programming languages (Qiskit, Cirq)
- Publication record in quantum machine learning or related fields
- Expertise in high-performance computing environments
- Strong background in linear algebra and quantum mechanics