NCX Engineer, AI Accelerator

Responsibilities

• Build and deploy custom AI solutions on NCP and Neo Cloud platforms, including distributed training, inference optimization, and MLOps pipelines.
• Act as the primary technical contact for strategic NCPs, providing remote and on-site support and troubleshooting complex production issues.
• Deploy and manage AI workloads across DGX Cloud, NCP data centers, and major CSP environments using Kubernetes, containers, and GPU scheduling systems.
• Profile and tune large-scale training and inference workloads to reduce latency, cost, and operational risk.
• Implement NVIDIA reference architectures on partner platforms and develop integrations with partner control planes and customer environments.
• Create detailed implementation guides, runbooks, and post-mortem documentation for running NVIDIA AI workloads at scale.

Requirements

• BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field.
• 8+ years of experience in customer-facing technical roles such as Solutions Engineering, DevOps, Site Reliability, or ML Infrastructure Engineering.
• Strong expertise in Linux systems, distributed computing, Kubernetes, containers, and GPU scheduling.
• Demonstrated AI/ML experience supporting large-scale training and inference workloads (e.g., LLMs, generative models, or recommendation systems).
• Solid programming skills in Python or Go.
• Hands-on experience using frameworks such as PyTorch or TensorFlow for training and serving.
• Excellent communication and technical presentation skills to articulate architectures and trade-offs to engineering and leadership audiences.

Preferred Qualifications

• Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, Triton, NIM, and networking technologies like InfiniBand or RoCE.
• Direct experience collaborating with NVIDIA Cloud Partners, hyperscale CSPs, or managed AI cloud platforms.
• Deep familiarity with MLOps and cloud-native practices, including CI/CD, observability stacks (Prometheus, Grafana, OpenTelemetry), and GitOps.
• Background in Infrastructure as Code (Terraform, Ansible) for deploying GPU-accelerated clusters.

About the Company

NVIDIA is a global leader in AI computing. We partner with the world's most innovative AI companies to address their most challenging technical problems, delivering groundbreaking AI workloads and advanced AI deployments.