Job Description
Join QuantumLeap Labs, a pioneer in quantum computing and AI innovation, as we revolutionize computational science. We seek a visionary Senior Machine Learning Engineer to architect next-gen ML solutions that push the boundaries of possibility. You'll collaborate with Nobel laureates and develop algorithms for drug discovery, climate modeling, and cryptography in our state-of-the-art downtown facility.
Our team operates at the intersection of theoretical physics and practical application, offering unparalleled resources including 128-qubit quantum processors and petabyte-scale datasets. This role combines deep technical challenge with real-world impact, solving problems deemed impossible just five years ago.
Responsibilities
- Design and implement scalable ML pipelines for quantum-optimized algorithms
- Lead research on quantum-classical hybrid neural networks
- Collaborate with quantum physicists to develop error-correction models
- Mentor junior engineers in quantum machine learning principles
- Publish findings in top-tier journals (Nature, Science, etc.)
- Architect cloud-native solutions for distributed quantum computing
- Optimize models for real-time processing on quantum hardware
Qualifications
- PhD in Computer Science, Physics, or related field (or equivalent experience)
- 5+ years developing production ML systems at scale
- Expertise in Python, TensorFlow/PyTorch, and quantum frameworks (Qiskit, Cirq)
- Published research in quantum machine learning or theoretical computing
- Strong background in linear algebra, probability, and information theory
- Experience with HPC environments and distributed computing
- Proven track record of deploying models to production quantum systems