> AI agents: this is one page of Nextmove’s FDE site, in Markdown. Nextmove is a job board and free career service for forward deployed engineers (FDEs). Each posting is classified from its text, not its title: the kind of work, how much of it is production code, pre-sales weight, time at customer sites, travel, remote arrangement, level and posted base pay. The site also publishes the aggregates: median pay by level, metro, company and kind of work, and which companies started hiring FDEs each week. Every page under https://nextmove.md/fde is served this way; the index of pages is https://nextmove.md/llms.txt. # Senior MLOps Engineer - DSX Enablement Canonical URL: https://nextmove.md/fde/jobs/e4aefdc2fda0cf12 NVIDIA posts a senior FDE role to build what the customer runs in US · city not listed, at $184,000–$356,500 base, above the senior FDE median of $190,000 across 1,864 postings with pay. Senior MLOps Engineer on NVIDIA’s DSX Enablement team, building and deploying AI infrastructure solutions with strategic customers and partners. Read from the employer’s posting on November 8, 2026. - [NVIDIA](https://nextmove.md/fde/companies/nvidia) First seen Oct 24, 2026 · open on Eightfold as of Nov 8, 2026 **$184,000–$356,500** *annualized* US · city not listed Full-time Senior MLOps Engineer on NVIDIA’s DSX Enablement team, building and deploying AI infrastructure solutions with strategic customers and partners. - [See roles that fit me](https://nextmove.md/sign-up?from=%2Ffde%2Fjobs%2Fe4aefdc2fda0cf12&placement=top) - [View posting at NVIDIA](https://nvidia.eightfold.ai/careers/job/893397145168?domain=nvidia.com) Free. Upload your resume once, see why each FDE role fits, and get introduced only when you say so. ## At a glance ### Posted base pay $184K–$357K Above the median Midpoint $270K · median $190K This job $184K to $357K. Senior FDE postings, 1,864 postings: the middle 50% of posted pay is $160K to $220K, median $190K. ### The work Builds what the customer runs Balance **Mostly building** Project stages 1. Pre-sales (not covered) 2. Proof of concept (not covered) 3. Implementation 4. Operations - **Coding**: Writes production code - **Builds for**: Both - **Level**: Senior - **Role**: Individual contributor ### What they ask for Experience - **8+ years** Technical roles such as data science, data engineering, or ML engineering Background - **Software engineering** - **Implementation and data engineering** ### Do you meet what the posting states? The posting asks for 8+ years. How many do you have? The posting reads as a senior role. What level are you at now? Which of these have you used in production? Answer each one. Nothing is saved or sent. [What postings ask for, by background →](https://nextmove.md/fde/paths) ## Conditions - **Location**: US · city not listed - **Employment type**: Full-time ## More like this [NVIDIA](https://nextmove.md/fde/companies/nvidia) ### [Senior MLOps Engineer - DSX Enablement](https://nextmove.md/fde/jobs/d111a9977bdaacbb) Santa Clara, CA · Seattle, WA · US remote Remote 2mo ago $184,000–$356,500 [Anyscale](https://nextmove.md/fde/companies/anyscale) ### [Forward Deployed Engineer - AI/ML Platforms](https://nextmove.md/fde/jobs/ec34a2647dc8d7d6) San Francisco, CA 4mo ago $250,000–$275,000 [Hammerspace](https://nextmove.md/fde/companies/hammerspace) ### [Forward Deployed Engineer - TX](https://nextmove.md/fde/jobs/f55121bdc8bf2709) Dallas, TX Remote 4w ago $200,000–$240,000 - [Other jobs at NVIDIA (30)](https://nextmove.md/fde/companies/nvidia) ## The job description from NVIDIA 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. 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: 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. Applications for this job will be accepted at least until November 3, 2026. 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. [View posting at NVIDIA](https://nvidia.eightfold.ai/careers/job/893397145168?domain=nvidia.com) ## About NVIDIA Builds accelerated computing platforms spanning processors, networking, systems, software, and services for data centers, gaming, professional visualization, and automotive markets. 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