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Senior MLOps Engineer - DSX Enablement

DE01 NVIDIA Germany

LocationGermany
Senioritysenior
CompanyDE01 NVIDIA Germany
Verified recentlyChecked today
Compensation

Salary not listed

Salary details are shown when available from the source listing. Sign in before applying so the role can be reviewed against your resume, salary goals, seniority, timezone, and location eligibility.

Requirements and working style

Decision details from the source listing

Experience

8+ years stated

Education

BS in Computer Science or related technical field, MS in Computer Science or related technical field, PhD in Computer Science or related technical field, Equivalent experience

Work authorization

Germany work authorization

Schedule

not specified

Benefits stated
Competitive salariesGenerous benefits package

These fields are normalized from the employer's text. Confirm details on the employer site before applying.

WFH.team analysis

What this posting tells you

Senior MLOps Engineer role at NVIDIA Germany for remote work across 5 locations in Germany. Requires 8+ years of experience in ML engineering or related data roles, strong skills in AI infrastructure and MLOps technologies, programming in Python and system languages, and familiarity with Kubernetes and deep learning frameworks. Education requirements include a degree in CS or related fields. The role involves advanced AI/ML system performance tuning and open-source tool development. Salary details are location-dependent but only given explicitly for Poland, not Germany. Position is full-time with competitive benefits.

Role lane

Backend, Customer success, Data, DevOps, Marketing, Security, Software, Customer support

Where you can work

Germany

Working hours

Europe/Berlin

Arrangement

senior · full_time

Required signals
MLOpsAI infrastructureMachine LearningPythonC++GoRustKubernetesLinuxDistributed systemsDeep learning frameworksBatch schedulersNetworkingScripting (bash)
Preferred signals
Open source contributionsNVIDIA ecosystem including DGX systems, CUDA, NeMo, RAPIDS, Triton, NIMSecurity-critical environment experienceCloud-native MLOps practicesCI/CD pipelinesWorkflow automationObservability stacksGitOps workflowsPerformance diagnosis spanning hardware to application stack
Confirm before applying
  • Compensation is not listed
Market context

Backend hiring on WFH.team

5,700active related roles
2,379new in the latest period
267.7jobs per 100 candidates
$204kmedian of comparable listed ranges

Category counts come from WFH.team's latest published remote job market snapshot.

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Skills and signals
MLOpsAI infrastructureMachine LearningPythonC++GoRustKubernetesLinuxDistributed systemsDeep learning frameworksBatch schedulersNetworkingScripting (bash)Open source contributionsNVIDIA ecosystem including DGX systems, CUDA, NeMo, RAPIDS, Triton, NIMRemote in Germany at multiple locations
Job description

Senior MLOps Engineer - DSX Enablement at DE01 NVIDIA Germany

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 the pay of employees in similar positions. For Poland: The base salary range is 292,500 PLN - 507,000 PLN for Level 4, and 375,000 PLN - 650,000 PLN for Level 5.

Company context

Working remotely at DE01 NVIDIA Germany

DE01 NVIDIA Germany is hiring for 6 active remote roles, with remote-friendly openings, application links, and job details refreshed from the public remote job inventory.

Remote policy

Remote hiring signal is inferred from active confirmed-remote job listings.

Research DE01 NVIDIA Germany