Senior MLOps Engineer - DSX Enablement

What you'll do

• Build and deploy custom AI solutions on NeoCloud platforms and NVIDIA Cloud Partners, including distributed training, inference optimization, and MLOps pipelines.
• Advise customers and partners, troubleshoot production systems, and tune workloads to reduce latency, cost, and operational risk.
• Develop open-source tools and reference architectures for managing AI and machine learning workloads at scale.

What they ask 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 technical roles such as data science, data engineering, or ML engineering.
• AI/ML experience across multiple phases of the machine learning lifecycle, plus experience using machine learning or deep learning frameworks for training and inference.
• Systems knowledge including Linux, batch schedulers, Kubernetes, distributed filesystems, advanced networking, and programming or scripting with bash, Python, and a systems language such as C++, Go, or Rust.

Nice to have

• Experience contributing to open-source communities.
• Experience with the NVIDIA ecosystem, security-critical machine learning systems, distributed training and inference frameworks, or cloud-native MLOps practices.

Pay

184,000 USD - 287,500 USD (base salary, Level 4); 224,000 USD - 356,500 USD (base salary, Level 5)

Tools

NeoCloud, NVIDIA Cloud Partners (NCPs), DGX Cloud, Linux, Kubernetes, Python, C++, CUDA

AI focus

Develop and optimize AI infrastructure and workloads, including distributed training, inference, MLOps pipelines, and LLM performance evaluation.