Deskripsi Pekerjaan
Apex Neural Systems is seeking an experienced Senior AI Infrastructure Engineer to architect, scale, and optimize distributed high-performance computing clusters for large-scale foundation model training and high-throughput real-time inference.
In this role, you will bridge the gap between machine learning research and bare-metal hardware orchestration, engineering resilient systems that handle multi-petabyte datasets and massive parallel compute workloads.
Tanggung Jawab
- Architect and maintain high-throughput, low-latency GPU cluster orchestration using Kubernetes and Ray.
- Optimize distributed deep learning training pipelines across multi-node NVIDIA H100 and B200 fabrics.
- Build fault-tolerant storage and data ingestion layers capable of sustained multi-terabyte model streaming.
- Implement automated cluster telemetry, proactive health checks, and rapid failover mechanisms.
- Collaborate with AI researchers to optimize CUDA kernels, distributed memory, and network topologies.
- Enforce rigorous security baselines, identity governance, and workload isolation across hybrid infrastructure.
Kualifikasi
- At least 5 years of engineering experience operating production distributed systems at scale.
- Proficiency in orchestrating large-scale distributed workloads using Kubernetes, Slurm, or Ray.
- Production experience configuring high-speed interconnects including InfiniBand, RoCE, and NVLink.
- Strong programming skills in Go, Python, or Rust.
- Deep operational familiarity with Linux kernel tuning, distributed file systems, and block storage.
- Direct experience managing multi-node accelerator clusters (NVIDIA GPUs, CUDA profiling).