ML Data Ops Lead: Dataset Releases & Reliability

NVIDIA Corporation; Santa Clara (CA); On-site; USD 168,000 - 322,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation is seeking an ML Data Operations Lead to own the customer-facing lifecycle of AV datasets. You will partner with ML engineers, translate data needs into release requirements, and coordinate across engineering and infrastructure to ensure timely, documented, and validated dataset releases.

The role emphasizes operational ownership over data pipelines, with a focus on delivering reliable, well-documented releases and clear communication to customers.

Qualifications

• Bachelor's degree or equivalent experience in a relevant field.
• 6+ years in ML data operations, technical service delivery, dataset operations, or related roles.
• Solid understanding of ML data lifecycle from collection to deployment.
• Ability to use SQL and data-analysis tools to investigate dataset contents.

Responsibilities

• Serve as the primary operational partner for ML engineers and internal data consumers.
• Capture and clarify dataset release requirements including use cases, signals, labels, and volumes.
• Coordinate release calendars, priorities, dependencies, and compute capacity across tracks.
• Monitor production release workflows from launch through delivery.
• Identify risks and drive cross-functional resolution with engineers and infra teams.
• Validate release results against expected data volumes and quality criteria.

Skills

ML data lifecycle

SQL

Customer-facing communication

Requirements gathering

Risk assessment

Cross-functional collaboration

Education

Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or related field

Tools

Python

Databricks

Notebooks

Job description

NVIDIA Corporation is seeking an ML Data Operations Lead to own the customer-facing lifecycle of AV datasets. You will partner with ML engineers, translate data needs into release requirements, and coordinate across engineering and infrastructure to ensure timely, documented, and validated dataset releases.

The role emphasizes operational ownership over data pipelines, with a focus on delivering reliable, well-documented releases and clear communication to customers.