Senior MLOps Engineer, DSX Enablement

What you'll do

• Build and deploy custom AI solutions on NeoCloud and NVIDIA Cloud Partner platforms.
• Develop and manage MLOps pipelines for distributed training and inference optimization.
• Profile and tune large-scale training and inference workloads to reduce latency and cost.
• Diagnose and solve full-stack AI and ML system problems in production environments.
• Develop open-source tools and reference architectures for managing machine learning workloads at scale.
• Act as a primary technical contact to guide joint engagements and ensure customer success.
• Work with infrastructure software teams to support accelerated frameworks for AI applications.

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 technical roles such as data science, data engineering, or ML engineering.
• Demonstrated AI/ML experience across multiple phases of the machine learning lifecycle, from exploratory analysis to production systems.
• Facility with systems topics including Linux, batch schedulers, Kubernetes, distributed filesystems, and advanced networking at datacenter scale.
• Solid scripting and programming skills in bash and Python and systems programming skills in C++, Go, or Rust.
• Experience using machine learning or deep learning frameworks for training and inference.
• Excellent communication and technical presentation skills to articulate architectures and trade-offs to engineering and leadership audiences.
• Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, RAPIDS, Triton, NIM, and networking technologies (preferred).