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Senior MLOps Engineer - DSX Enablement

NVIDIA nvidia.com Open
Remote Germany Full-time Senior ML Platform & Ops

At a glance

Senior ML Platform & Ops role at NVIDIA. Remote, Germany · full-time.

In listing ML Platform & Ops salary

RoleML Platform & Ops
SenioritySenior
LocationGermany
WorkplaceRemote
EmploymentFull-time
PostedOct 31, 2026
Role brief

remoteroles summary, based on the employer's posting.

What you'll do

  • Build and launch tailored AI workloads on NeoCloud and NVIDIA Cloud Partner platforms, including distributed training and MLOps pipelines
  • Serve as the technical point person for customers and partners, steering engagements and fixing production problems around DGX Cloud
  • Measure and tune training and inference workloads on partner platforms to cut latency, expense and operational risk
  • Develop open-source tools and reference architectures for operating ML workloads and pipelines at scale
  • Coordinate with infrastructure software and accelerated-framework teams to support AI applications and new hardware

What you bring

  • A computer science or computer/electrical engineering degree, a related technical qualification, or equivalent experience
  • At least eight years in technical work such as data science, data engineering or ML engineering, preferably on large production systems
  • AI/ML experience across several lifecycle stages, from exploratory analysis through production systems
  • Systems knowledge covering Linux, Kubernetes and batch schedulers, plus distributed storage or datacenter networking
  • Programming ability in bash or Python and systems languages such as C++, Go or Rust

Who this fits

This senior role suits an engineer who can troubleshoot issues across AI and ML systems and explain architecture choices to both engineering and leadership audiences. The position is remote in Germany and involves working with internal and external customers and partners.

From the employer

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. We partner with the world's most innovative AI companies and open-source communities to address their most challenging technical problems. ​

What you'll be doing:

In this role, you will develop innovative solutions that advance AI infrastructure capabilities, advise infrastructure experts on the demands of ML workloads, help practitioners diagnose and solve full-stack AI and ML system problems, and work on a team with 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. You will:

  • Build and deploy custom AI solutions on NeoCloud platforms and NVIDIA Cloud Partners (NCPs), including distributed training, inference optimization, and MLOps pipelines,

  • Act as a primary technical contact for internal and external customers and partners, guiding joint engagements, ensuring the success of initiatives on DGX Cloud, and solving complex problems in production,

  • Work closely with the teams building the infrastructure software and accelerated frameworks that support today’s most compelling AI applications,

  • Profile and tune large-scale training and inference workloads on NCP platforms, leading efforts to reduce latency, cost, and operational risk, and

  • Develop open-source tools and reference architectures to make it easier to build and manage machine learning and AI workloads, pipelines, and systems at scale.

What we need to see:

  • 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, ideally targeting large‑scale production systems.

  • 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 languages like bash and Python and solid systems programming skills in a language like C++, Go, or Rust.

  • Experience using machine learning or deep learning frameworks for training and inference.

  • Excellent communication and technical presentation skills, with the ability to clearly articulate architectures, trade‑offs, and recommendations to both engineering and leadership audiences.

  • A clear record of engineering discipline and execution on interesting projects, whether you’re working alone or collaborating on a team.

Ways to stand out from the crowd:

  • Experience contributing to and working in open-source communities.

  • Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, RAPIDS, Triton, NIM, and NVIDIA networking technologies such as InfiniBand, NVLink, and RoCE.

  • Experience and familiarity building machine learning systems in a security-critical environment and distributed training and inference frameworks.

  • Familiarity with MLOps practices in a cloud‑native context: containerization, CI/CD pipelines, workflow automation, observability stacks, and GitOps workflows.

  • Direct experience drawing on deep systems knowledge to diagnose and fix performance or correctness problems that span multiple layers of the application stack, like hardware, networking, accelerator, hypervisor or OS, compilers or runtimes, application code, and libraries.

NVIDIA offers competitive salaries and a generous benefits package. It is recognized as one of the technology world’s most desirable employers. We have some of the most innovative and dedicated people working here. Due to rapid growth, our outstanding teams are expanding quickly. Join us to make a lasting impact on the world!

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
Germany: 112,200 EUR – 194,480 EUR for Level 4; and 141,900 EUR – 245,960 EUR for Level 5.
Czechia: 1,537,500 CZK – 2,665,000 CZK for Level 4; and 2,025,000 CZK – 3,510,000 CZK for Level 5.
Poland: 292,500 PLN – 507,000 PLN for Level 4; and 375,000 PLN – 650,000 PLN for Level 5.
Opportunity

ML Platform & Ops work from LinkedIn, X, Reddit and Upwork, in one list.

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ML Platform & OpsRemote

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Opportunity

ML Platform & Ops work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind remoteroles.