Senior Machine Learning Data Pipeline Engineer

NVIDIA is hiring a Senior Machine Learning Data Pipeline Engineer in Santa Clara, United States. Level rates it ; you can apply on NVIDIA.

Level's read on this job

Level rates this role Builds AI ●●●●: the job is building AI systems.
The posting mentions AI agents among its tools and skills.
Level classes it as a senior role.
NVIDIA has 2,800+ other open roles on Level.
Posted in the last few days.

AI in this role

ai-agents

We are hiring a Senior Machine Learning Data Pipeline Engineer to invent and build the next generation of data pipelines for end-to-end autonomous driving foundation models. You will develop scalable pipelines and agentic workflows that help DNN teams proactively identify data gaps and efficiently discover, prepare, and deliver the right training data.

You will convert model limitations and data needs into reusable engineering solutions, integrating data infrastructure with LLMs, vision-language models, and retrieval techniques to automate data solutions.

What you'll be doing:

Design, build, and own scalable data pipelines that automate data discovery, selection, and curation to meet DNN training data needs.
Develop agentic workflows that proactively identify model data needs, plan and implement mining tasks using data tools and model inference, and refine mining strategies through human review and downstream model feedback.
Deploy and operate these pipelines and workflows as reliable production systems, with workflow orchestration, monitoring, and failure recovery.
Partner with MLEs and data analysts to turn recurring data needs and model failure cases into reusable mining capabilities, define acceptance criteria, and improve scenario coverage through feedback.

What we need to see:

BS or MS in Computer Science, Mathematics or Electrical Engineering, or a related quantitative field, or equivalent experience, plus 5+ years in software or data engineering.
Strong Python and SQL skills, shown through production services, APIs, or data pipelines.
Hands-on development of data solutions and optimization, including diagnosing DNN model performance and reliability issues.
Ability to develop and analyze automatic workflows that connect LLMs to tools and data services, including tool calling and workflow state management.
Solid understanding of deep learning, embeddings, and LLM/VLM inference, including how training datasets are prepared and consumed by DNN teams.
Shown experience in delivering data solutions starting from unclear requirements through to production, involving setting acceptance criteria alongside DNN engineers and data specialists and confirming outcomes.

Ways to Stand Out from the Crowd:

Hands-on work on foundation model data and training pipelines, including smaller-scale models built from scratch.
A track record of shipping LLM/VLM-based mining, multimodal retrieval, or curation services.
Background in autonomous driving or robotics data, including temporal video, sensor metadata, scenario definitions, or model failure analysis.

#AutonomousVehicles

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 10, 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.

How we rate this

Senior Machine Learning Data Pipeline Engineer at NVIDIA rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Machine Learning Data Pipeline Engineer is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in US, CA, Santa Clara.
The job was posted on November 6, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agents

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: AI agents. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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