Job Description
Join QuantumLeap Technologies at the forefront of 2026's AI revolution! We're seeking a visionary AI Infrastructure Engineer to architect, deploy, and optimize next-generation AI systems that will power humanity's technological leap forward. This role is critical in building the scalable, secure, and high-performance infrastructure for our groundbreaking AI initiatives.
As a pioneer in quantum-entangled computing and neural network optimization, you'll work with cutting-edge technologies to solve complex challenges in machine learning infrastructure. Our team operates at the intersection of theoretical physics and practical AI deployment, creating systems that learn, adapt, and evolve beyond current limitations.
Responsibilities
- Architect and deploy distributed AI computing systems leveraging quantum-inspired algorithms
- Optimize neural network performance on next-gen hardware (neuromorphic processors, photonic accelerators)
- Implement robust MLOps pipelines for autonomous model training and deployment
- Design security frameworks for AI systems operating in post-quantum cryptographic environments
- Develop real-time inference engines for edge and cloud-native AI applications
- Collaborate with quantum research teams to hybridize classical and quantum machine learning workflows
- Lead infrastructure scaling for petabyte-scale AI training datasets
Qualifications
- 5+ years in high-performance computing or distributed systems architecture
- Expertise in Kubernetes, Docker, and cloud-native AI deployment (AWS/GCP/Azure)
- Advanced knowledge of deep learning frameworks (PyTorch/TensorFlow) and GPU/TPU optimization
- Experience with MLOps tools (MLflow, Kubeflow, Airflow) and CI/CD for ML pipelines
- Strong background in container orchestration and microservices architecture
- Understanding of quantum computing principles and quantum machine learning algorithms
- Proven track record in building secure, scalable AI infrastructure at enterprise scale
- PhD in Computer Science/Engineering or equivalent practical experience