Senior MLOps Engineer - DSX Enablement

What you’ll do

• Build and deploy custom AI solutions on NeoCloud platforms and NVIDIA Cloud Partners (NCPs), including distributed training, inference optimization, and MLOps pipelines.
• Act as primary technical contact for internal and external customers, guiding joint engagements and ensuring success of initiatives on DGX Cloud.
• Profile and tune large-scale training and inference workloads on NCP platforms to reduce latency, cost, and operational risk.
• Develop open-source tools and reference architectures for building and managing ML/AI workloads at scale.

What you’ll bring

• BS, MS, or Ph.D. in CS, CE, EE, or related field, or equivalent experience.
• 8+ years in data science, data engineering, or ML engineering, ideally on large-scale production systems.
• Demonstrated AI/ML experience across the ML lifecycle, from exploratory analysis to production.
• Facility with Linux, batch schedulers, Kubernetes, distributed filesystems, and datacenter-scale networking.

Technologies

MLOps · Kubernetes · Python · C++ · Go · Rust · CUDA · NeMo · RAPIDS · Triton · NIM · InfiniBand

About NVIDIA

Designs and manufactures GPUs and system-on-chips powering data centers, AI workloads, gaming, autonomous vehicles, and HPC. The foundational hardware for modern deep learning.

Public