Job Description
Join QuantumLeap Labs at the intersection of quantum computing and artificial intelligence. We're pioneering next-gen solutions for Fortune 500 clients in biotech, finance, and climate science. As a Senior Machine Learning Engineer, you'll architect scalable ML systems that process petabytes of scientific data and deploy cutting-edge quantum algorithms. Our culture values intellectual curiosity, collaborative innovation, and breakthrough thinking. If you're passionate about pushing the boundaries of computational science, this is your opportunity to shape the future.
Responsibilities
- Design and implement quantum-enhanced ML pipelines for complex scientific datasets
- Lead research on quantum machine learning algorithms and hybrid classical-quantum models
- Collaborate with PhD researchers to translate theoretical concepts into production-ready systems
- Optimize ML models for quantum hardware constraints while maintaining performance
- Develop automated MLOps pipelines for continuous model training and deployment
- Publish research in top-tier conferences (NeurIPS, ICML, QIP) and contribute to open-source projects
- Mentor junior engineers and conduct technical workshops on quantum ML topics
Qualifications
- PhD or Master's in Computer Science, Physics, or Mathematics with 5+ years ML experience
- Expertise in Python, TensorFlow/PyTorch, and quantum programming frameworks (Qiskit, Cirq)
- Proven track record of deploying ML models at scale (AWS/GCP/Azure)
- Strong background in linear algebra, probability theory, and quantum mechanics
- Experience with high-performance computing and distributed systems
- Publications in ML or quantum computing conferences preferred
- Excellent communication skills for collaborating with cross-disciplinary teams
- Passion for ethical AI development and scientific reproducibility