Job Description
Join QuantumLeap Dynamics at the forefront of technological evolution! We're seeking a visionary Senior AI Research Engineer to architect next-generation solutions that will redefine industries by 2026. As a key innovator in our Austin R&D hub, you'll collaborate with Nobel laureates and disrupt traditional paradigms through quantum-inspired machine learning and neuromorphic computing.
Our lab operates at the intersection of AI, biotechnology, and sustainable energy, with projects including climate-predictive neural networks and ethical AGI frameworks. You'll lead research initiatives with unlimited compute resources and publish in Nature/Science journals while mentoring the next generation of pioneers.
Benefit from our future-proof compensation structure, including equity in quantum-resistant blockchain ventures and unlimited sabbatical programs. Shape tomorrow's reality today.
Responsibilities
- Design and implement cutting-edge AI architectures for 2026-era applications
- Lead cross-disciplinary research teams in quantum machine learning development
- Pioneer ethical AI frameworks for autonomous systems and biotech applications
- Develop patent-pending algorithms for climate modeling and sustainable energy optimization
- Mentor junior researchers in neuromorphic computing and quantum-resistant cryptography
- Collaborate with Fortune 500 partners on real-world deployment of AI solutions
- Present breakthrough findings at global tech summits and peer-reviewed publications
Qualifications
- PhD in Computer Science, AI, or related field with 5+ years industry experience
- Expertise in transformer architectures, federated learning, and quantum algorithms
- Publication record in top-tier AI conferences (NeurIPS, ICML, ICLR)
- Proficiency in PyTorch, TensorFlow Quantum, and neuromorphic hardware (Loihi, TrueNorth)
- Deep understanding of ethical AI frameworks and regulatory compliance (EU AI Act)
- Experience deploying AI at edge devices with sub-5ms latency requirements
- Strong background in computational biology or climate modeling preferred