Job Description
Join QuantumLeap Dynamics at the forefront of technological evolution as we pioneer solutions for 2026's most critical challenges. We're seeking an AI Research Engineer to architect next-generation neural networks that will redefine human-machine interaction. Our Austin-based innovation hub combines cutting-edge R&D with real-world deployment in healthcare, climate modeling, and autonomous systems. Enjoy competitive equity, flexible work arrangements, and direct impact on projects shaping humanity's digital future.
Responsibilities
- Design and implement novel deep learning architectures for predictive modeling
- Lead cross-functional teams in deploying AI solutions across enterprise platforms
- Research and integrate emerging quantum computing frameworks into neural networks
- Develop ethical AI governance frameworks for 2026 regulatory compliance
- Collaborate with MIT and Stanford on next-gen human-AI symbiosis protocols
- Optimize model performance for edge deployment in IoT ecosystems
- Author white papers for IEEE journals on 2026 AI paradigms
Qualifications
- PhD in Machine Learning or equivalent research experience
- 5+ years implementing production-level neural networks (Transformer, GNN)
- Published work in top-tier AI conferences (NeurIPS, ICML)
- Expertise in quantum machine learning frameworks (Qiskit, Cirq)
- Strong background in federated learning and differential privacy
- Proven track record of scaling models to 100M+ parameter systems
- Experience with MLOps tools (MLflow, Kubeflow)