Senior MLOps Engineer - DSX Enablement
Originally posted 2 September 2026 by the employer — open 20 days.
About the role
This role involves developing solutions to advance AI infrastructure capabilities and advising on the demands of ML workloads for strategic customers.
What you'll do
- Develop innovative solutions to advance AI infrastructure capabilities.
- 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 on DGX Cloud.
- Profile and tune large-scale training and inference workloads on NCP platforms to reduce latency, cost, and operational risk.
- Develop open-source tools and reference architectures for building and managing machine learning and AI workloads, pipelines, and systems at scale.
What you'll need
- 8+ years of experience in technical roles such as data science, data engineering, or ML engineering, targeting large-scale production systems.
- 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.
- Solid systems programming skills in a language like C++, Go, or Rust.
- Experience using machine learning or deep learning frameworks for training and inference.
Skills: MLOps Engineer, AI workloads, AI infrastructure capabilities, ML workloads, DGX Cloud, CUDA, NeMo, RAPIDS, Triton, NIM
This role has been open 20 days — well below the 67-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
522
|
Median days open
67 d
|
Median salary
$235k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | NVIDIA | All employers we track in this specialty (522 roles · 76 employers) |
|---|---|---|
| Open roles in this specialty | 84 | 522 |
| Open roles in the wider Software, Firmware & Systems family | 963 | 5873 · 143 employers |
| Median days open | 62 d | 67 d (−5 d vs this employer) |
| Median salary (USD postings) | — | $235k |
Skills observed across this category: MLOps Engineer, AI workloads, AI infrastructure capabilities, ML workloads, DGX Cloud, CUDA
Who's hiring in this category
- Qualcomm · 107 open roles · median 97 d
- NVIDIA (this employer) · 86 open roles · median 68 d
- AMD · 46 open roles · median 60 d
- Micron Technology · 32 open roles · median 40 d
- Mobileye · 25 open roles · median 54 d
- Analog Devices · 14 open roles · median 25 d
How we counted: 522 open AI/ML Hardware Engineering (AI ML Hardware) roles from 76 employers tracked in the SemiconductorJobs index, counted 22 Sept 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.