Senior MLOps Engineer - DSX Enablement

NVIDIA; United States; Remote; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Senior MLOps Engineer to join the DSX Enablement team to collaborate with strategic customers on AI workloads. You will build and optimize ML pipelines, train and deploy at scale on NeoCloud and NCP platforms, and act as the technical lead for joint engagements across DGX Cloud.

The role requires 8+ years in ML engineering or related fields and strong Linux/Kubernetes experience, plus proficiency in Python and C++/Go/Rust. Equity and comprehensive benefits are offered.

Qualifications

• BS, MS, or Ph.D. in CS, CS/EE, or related field, or equivalent experience.
• 8+ years in data science, data engineering, or ML engineering for large-scale systems.
• Experience across ML lifecycle from exploration to production.
• Proficiency with Linux, Kubernetes, distributed filesystems, and datacenter networking.
• Strong scripting and programming: Bash, Python; systems programming in C++, Go, or Rust.
• Experience with ML/DL frameworks for training and inference.

Responsibilities

• Develop innovative AI infrastructure solutions.
• Advise infrastructure teams on ML workloads.
• Diagnose and solve full-stack AI/ML system problems.
• Lead AI/ML initiatives on DGX Cloud and NCPs.
• Build and deploy AI solutions on NeoCloud platforms.
• Be primary technical contact for customers and partners.
• Profile and tune large-scale training and inference workloads.
• Develop open-source tools and reference architectures.

Skills

Linux

Kubernetes

Python

C++

Go

Rust

ML frameworks

Distributed training

Education

BS/MS/PhD in CS/EE or related

Tools

CUDA

NeMo

RAPIDS

Triton

DGX

Job description

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 will 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,
• 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. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.