Senior MLOps Engineer - DSX Enablement

In this role you will design and deploy AI infrastructure solutions, guiding customers through production ML workloads and Open-source projects. You’ll optimize training and inference at scale on NVIDIA platforms, collaborating with cross-functional teams to deliver reliable, scalable AI pipelines. You’ll shape open-source tooling and reference architectures to simplify building and managing ML workloads. This position offers the chance to impact enterprise and partner AI initiatives across DGX Cloud and NCP ecosystems.

• Build and deploy custom AI solutions on NeoCloud and NVIDIA Cloud Partners (NCPs) enabling distributed training and MLOps pipelines
• Serve as primary technical contact for customers and partners, guiding engagements and ensuring success on DGX Cloud initiatives
• Collaborate with infrastructure software and accelerated frameworks teams to support AI applications
• Profile and optimize large-scale training and inference workloads on NCP platforms to reduce latency, cost, and risk
• Develop open-source tools and reference architectures for scalable ML workloads and pipelines

• 8+ years in data science, data engineering, or ML engineering for large-scale production systems
• Proficiency with Linux, batch schedulers, Kubernetes, distributed filesystems, and datacenter networking
• Strong scripting with Bash and Python; systems programming in C++, Go, or Rust
• Experience with ML/DL frameworks for training and inference
• Excellent written and verbal communication for technical audiences
• Track record of engineering discipline and execution, solo or in teams

• strong communication
• ability to articulate architectures and trade-offs
• collaboration with cross-functional teams
• Linux
• Kubernetes
• distributed filesystems