Job Description
Join QuantumLeap Dynamics, where we're pioneering the next frontier of quantum computing applications. As a Senior Machine Learning Engineer, you'll architect and deploy cutting-edge AI solutions that solve complex scientific challenges. Collaborate with world-class researchers to transform theoretical models into scalable production systems that impact industries from pharmaceuticals to renewable energy.
We offer competitive compensation, equity packages, and a flexible work environment that values innovation and work-life balance. Your work will directly contribute to breakthroughs in computational science while mentoring junior engineers and shaping our technical roadmap.
Responsibilities
- Design and implement ML pipelines for quantum algorithm optimization
- Collaborate with research scientists to translate theoretical models into production-ready systems
- Lead development of distributed computing frameworks for large-scale scientific simulations
- Optimize model performance using advanced techniques like federated learning and neural architecture search
- Conduct rigorous A/B testing and statistical analysis to validate scientific hypotheses
- Mentor junior engineers and contribute to open-source scientific computing projects
- Present findings at technical conferences and publish in peer-reviewed journals
Qualifications
- PhD in Computer Science, Physics, or related field with 5+ years industry experience
- Expertise in Python, TensorFlow/PyTorch, and high-performance computing frameworks
- Strong background in quantum computing algorithms or computational physics
- Proven track record of deploying ML models at scale in scientific domains
- Experience with cloud platforms (AWS/GCP/Azure) and container orchestration
- Publication record in top-tier ML or physics conferences (NeurIPS, ICML, etc.)
- Deep understanding of statistical modeling and experimental design principles