Senior MLOps Engineer, DSX Enablement

What you'll do

• Build and deploy custom AI solutions including distributed training, inference optimization, and MLOps pipelines on NeoCloud platforms.
• Act as the primary technical contact for internal and external customers to guide joint engagements and solve production problems.
• Profile and tune large-scale training and inference workloads to reduce latency, cost, and operational risk.
• Develop open-source tools and reference architectures to simplify managing machine learning workloads at scale.
• Diagnose and resolve full-stack AI and ML system problems across hardware, networking, and software layers.
• Support new hardware in open-source frameworks and perform LLM performance evaluations.
• Collaborate with infrastructure teams to improve the software and accelerated frameworks supporting 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 for large-scale production systems.
• Demonstrated AI/ML experience across the full machine learning lifecycle from exploratory analysis to production.
• Proficiency with Linux, batch schedulers, Kubernetes, distributed filesystems, and advanced networking at datacenter scale.
• Strong scripting skills in Bash and Python, plus 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, open-source communities, or MLOps practices in a cloud-native context (preferred).