Senior Machine Learning Data Pipeline Engineer

Nvidia Corporation in; Santa Clara (CA); Presencial; USD 140.000 - 270.000; Tempo integral

Benefícios oferecidos por esta vaga

Equity

Benefits

Resumo da vaga

NVIDIA Corporation is hiring a Senior Machine Learning Data Pipeline Engineer in Santa Clara, CA. You will design scalable data pipelines, build agentic workflows, and deploy production systems to support end-to-end autonomous driving foundation models.

You will collaborate with MLEs and data analysts, translate data needs into reusable mining capabilities, and help improve model data coverage through feedback and automation. Equity and comprehensive benefits accompany the role.

Qualificações

• BS or MS in Computer Science, Mathematics or Electrical Engineering, or equivalent experience.
• 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.

Responsabilidades

• Design, build, and own scalable data pipelines that automate data discovery, selection, and curation for DNN training data needs.
• Develop agentic workflows to identify model data needs and plan mining tasks using data tools and model inference.
• Deploy and operate pipelines as production systems with monitoring and failure recovery.
• Partner with MLEs and data analysts to turn data needs into reusable mining capabilities and improve coverage.

Conhecimentos

Python

SQL

Data pipelines

LLM/embedding concepts

Production services

Workflow automation

Formação

BS in Computer Science

MS in Computer Science or Electrical Engineering

Mathematics or related field

Ferramentas

APIs

Workflow orchestration

Descrição da vaga

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

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: 140,000 USD – 224,250 USD for Level 3; and 168,000 USD – 270,250 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 11, 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.

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