Job Description
Join QuantumLeap Systems at the forefront of AI infrastructure innovation for 2026. We're seeking a visionary AI Infrastructure Engineer to architect next-generation systems that will power the next wave of artificial intelligence breakthroughs. In this role, you'll design scalable, high-performance computing environments optimized for large-scale machine learning models while pioneering sustainable energy-efficient solutions.
You'll collaborate with world-class researchers to implement cutting-edge hardware acceleration strategies, optimize distributed training workflows, and develop novel cooling technologies for next-gen AI chips. This is your opportunity to shape the physical infrastructure that will enable AGI development while reducing environmental impact.
Responsibilities
- Design and implement petabyte-scale AI training infrastructure using NVIDIA H100 and next-gen quantum processors
- Develop liquid cooling systems for 1MW+ GPU clusters targeting 70% PUE efficiency
- Architect distributed training frameworks supporting 10,000+ GPU parallelism
- Create fault-tolerant systems with sub-100ms failover for mission-critical AI workloads
- Optimize data pipelines achieving 10TB/s throughput for real-time model inference
- Lead zero-carbon computing initiatives using geothermal and hydrogen fuel cell power
- Maintain 99.999% system uptime across global AI research facilities
Qualifications
- MS/PhD in Computer Engineering, Quantum Computing, or related field with 5+ years experience
- Expertise in CUDA programming and NVIDIA Mellanox networking stack
- Proven track record designing 1MW+ data center cooling systems
- Deep knowledge of quantum error correction and fault-tolerant architectures
- Experience with Kubernetes, Spack, and Slurm at supercomputing scale
- Certification in green data center design (LEED/EDGE)
- Published research in high-performance computing or quantum systems