NCX Senior Engineer

What you'll do

• Build and deploy custom AI solutions including distributed training, inference optimization, and MLOps pipelines on NCP and Neo Cloud platforms.
• Act as the main technical contact for strategic partners to troubleshoot complex production problems and provide remote or on-site support.
• Deploy and manage AI workloads across DGX Cloud and 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 observability and SLO/SLA monitoring for AI workloads.
• Develop integrations with partner control planes and ensure smooth API, data pipeline, and enterprise software connectivity.
• Create implementation guides, runbooks, and post-mortem documentation to codify standard methodologies for running AI workloads at scale.

What we're looking for

• BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
• 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 on multi-tenant or service-provider platforms.
• Demonstrated AI/ML experience supporting large-scale training and inference workloads in production or critically important environments.
• Solid programming skills in Python/Go with hands-on experience using frameworks such as PyTorch or TensorFlow.
• Excellent communication and technical presentation skills to articulate architectures and recommendations to engineering and leadership audiences.
• Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, Triton, NIM, and InfiniBand or RoCE (preferred).
• Direct experience collaborating with NVIDIA Cloud Partners, hyperscale CSPs, or managed AI cloud platforms (preferred).