ML Data Operations Lead, Dataset Release and Delivery - Autonomous Vehicles

NVIDIA
Santa Clara, Boulder
Full timeUSD 168,000 - 322,000 annuallyFunction: Business OperationsExperience: 6+ yearsEducation: bachelorsSkills: ["Customer orientation","Written communication","Judgment","Influencing without authority","Risk management"]

Own the customer-facing operational lifecycle for AV dataset releases, partnering with ML engineers to capture release requirements and translate them into execution plans. Coordinate concurrent dataset-release tracks by managing calendars, dependencies, engineering readiness, and compute capacity. Monitor workflows end-to-end, troubleshoot failures and delivery risks, validate results against expected quality and volumes, and communicate status through release notes, incident summaries, and handoff documentation.

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FursaFursa
NVIDIA
NVIDIA
4 days ago

ML Data Operations Lead, Dataset Release and Delivery - Autonomous Vehicles

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 5 hours agoStatus: Live

Job Summary

Own the customer-facing operational lifecycle for AV dataset releases, partnering with ML engineers to capture release requirements and translate them into execution plans. Coordinate concurrent dataset-release tracks by managing calendars, dependencies, engineering readiness, and compute capacity. Monitor workflows end-to-end, troubleshoot failures and delivery risks, validate results against expected quality and volumes, and communicate status through release notes, incident summaries, and handoff documentation.
Location: Santa Clara, Boulder
Employment Type: Full time
Job Function: Business Operations
Seniority: Mid level

Key Responsibilities

  • •Act as the primary operational partner for ML engineers and internal consumers of AV datasets.
  • •Capture and clarify dataset release requirements, including use cases, signals/labels, data volumes, release cadence, timelines, storage destinations, and acceptance criteria.
  • •Own the release calendar and coordinate priorities, dependencies, engineering readiness, and compute capacity across multiple concurrent release tracks.
  • •Monitor production release workflows, identify failures and risks (resource constraints, missing data), and drive resolution with engineers and infrastructure owners.
  • •Validate release results against expected volumes, versions, and quality criteria and communicate release status, risks, incidents, recovery plans, and documentation to customers.

Pay and Benefits

Salary: USD 168,000 - 322,000 annually
Equity and Bonus:Equity

Key Requirements

  • •Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent experience.
  • •6+ years of experience in ML data operations, technical service delivery, dataset operations, release operations, technical program execution, or another data-intensive operational role.
  • •Solid understanding of the machine learning data lifecycle: collection, curation, labeling, validation, versioning, release, storage, and consumption by training/evaluation pipelines.
  • •Ability to use SQL and data-analysis tools to investigate dataset contents and identify quality or completeness issues.
  • •Strong customer orientation and written communication to produce requirements, release notes, status updates, incident summaries, and operating procedures.
Experience:6+ yearsMachine learningData-intensive operationsDataset operationsAutonomous vehiclesADASComputer vision
Education:Bachelor's
Skills:Customer orientationWritten communicationJudgmentInfluencing without authorityRisk management
Tech Stack:SQLPythonDatabricksNotebooksDashboards

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
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