Senior MLOps Engineer - DSX Enablement
€112k - €194k • Remote • Germany, Remote • Full-time
Posted 12h ago
Job Location
Germany, Remote
Also open in US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
NVIDIA is seeking a Senior MLOps Engineer to join our DSX Enablement team, collaborating closely with strategic customers to implement and enhance groundbreaking AI workloads. You will develop innovative solutions that advance AI infrastructure capabilities, advise infrastructure experts on the demands of ML workloads, and help practitioners diagnose and solve full-stack AI and ML system problems. This role involves direct responsibility for the success of internal and external customers’ AI and ML initiatives, including LLM performance evaluation and supporting new hardware in open-source frameworks.
Responsibilities
- Build and deploy custom AI solutions on NeoCloud platforms and NVIDIA Cloud Partners, including distributed training, inference optimization, and MLOps pipelines.
- Serve as a primary technical contact for customers and partners, guiding joint engagements and ensuring success on DGX Cloud.
- Collaborate with teams building infrastructure software and accelerated frameworks for AI applications.
- Profile and tune large-scale training and inference workloads on NVIDIA Cloud Partner platforms to reduce latency, cost, and operational risk.
- Develop open-source tools and reference architectures for building and managing machine learning and AI workloads at scale.
Requirements
- BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or equivalent experience.
- 8+ years of experience in technical roles such as data science, data engineering, or ML engineering, targeting large-scale production systems.
- Demonstrated AI/ML experience across multiple phases of the machine learning lifecycle.
- Proficiency with systems topics including Linux, batch schedulers, Kubernetes, distributed filesystems, and advanced networking.
- Solid scripting and programming skills in Python and bash.
- Solid 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.
Benefits
- Competitive salaries
- Generous benefits package