Job Description
Join QuantumLeap Technologies at the forefront of 2026's AI revolution. We're pioneering next-generation machine learning infrastructure that will redefine how humanity interacts with artificial intelligence. As an AI/ML Infrastructure Engineer, you'll architect scalable systems powering breakthrough AI applications while ensuring ethical deployment and quantum-resistant security. Our Austin hub collaborates with global teams to build the computational backbone for tomorrow's autonomous systems, biotech simulations, and predictive analytics platforms.
Responsibilities
- Design and implement distributed ML training pipelines for petabyte-scale datasets
- Optimize GPU/TPU clusters for 2026-era AI model architectures
- Develop quantum-safe encryption protocols for model transfer
- Create automated MLOps pipelines with zero-downtime deployments
- Architect federated learning systems for cross-organization collaboration
- Implement real-time inference serving for edge-cloud hybrid deployments
- Conduct performance benchmarking for next-gen hardware accelerators
Qualifications
- 5+ years building production ML infrastructure at scale (Kubernetes, Spark, Kubeflow)
- Expertise in distributed computing frameworks (Ray, Horovod, Dask)
- Proficiency with GPU/TPU optimization and low-level programming (CUDA, Triton)
- Experience with quantum-resistant cryptography implementations
- Strong background in model security and adversarial defense techniques
- Published research in AI infrastructure or distributed systems (preferred)
- Ability to design solutions for 10M+ parameter models at inference scale