Senior MLOps Engineer

NVIDIA
Santa Clara
Workplace: OnsiteFull timeUSD 184,000 - 356,500 annuallyFunction: Solutions Engineering & Sales EngineeringExperience: 8+ yearsSkills: ["Ownership","Customer focus","Engineering judgment","Communication","Accountability"]

Build and operate end-to-end cloud pipelines for NVIDIA’s autonomous driving data and ML workflows. Ingest, validate, process, label, and transform multimodal sensor data (camera, lidar, radar) into training, evaluation, and validation datasets for L2–L4 autonomy. Own MLOps systems for model training, ground truth generation, and continuous evaluation, translating program and customer requirements into reliable, observable production systems across distributed teams.

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FursaFursa
NVIDIA
NVIDIA
2 days ago

Senior MLOps Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 22 hours agoStatus: Live

Job Summary

Build and operate end-to-end cloud pipelines for NVIDIA’s autonomous driving data and ML workflows. Ingest, validate, process, label, and transform multimodal sensor data (camera, lidar, radar) into training, evaluation, and validation datasets for L2–L4 autonomy. Own MLOps systems for model training, ground truth generation, and continuous evaluation, translating program and customer requirements into reliable, observable production systems across distributed teams.
Location: Santa Clara
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Design, build, and operate data pipelines supporting autonomous driving technology from L2 through L4.
  • •Own cloud pipeline architecture, implementation, and operations for ingesting, processing, labeling, and validating sensor data.
  • •Build observable MLOps systems for model training, ground truth generation, and continuous evaluation at AV scale.
  • •Translate customer and program requirements into production systems across perception, ML, data labeling, infrastructure, and product teams.
  • •Deliver technical direction, roadmaps, metrics, and operational benchmarks; contribute via reviews, debugging, and mentorship.

Pay and Benefits

Salary: USD 184,000 - 356,500 annually
Equity and Bonus:Equity

Key Requirements

  • •Bachelor’s or equivalent experience, and/or Master’s, or PhD in Computer Science, Electrical Engineering, or a related field (or equivalent experience).
  • •8+ years of engineering experience designing and delivering production distributed systems.
  • •Experience with MLOps, data pipelines, and cloud distributed systems.
  • •Proficiency in Python and C++ for system-level and performance-critical implementation.
  • •Ability to operate end-to-end data or ML pipelines with reliability, scale, and observability.
Experience:8+ yearsAutonomous vehiclesRoboticsComputer visionDeep learningGPU-accelerated computing
Education:
Skills:OwnershipCustomer focusEngineering judgmentCommunicationAccountability
Tech Stack:PythonC++Distributed systemsCloud infrastructureCI/CDData pipelinesMLOpsWorkflow orchestration

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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