Senior Manager, Machine Learning Ops Engineering - Automotive

Invidia

Santa Clara, CA, United States
Base: 272,000 usd - 431,250 usd; bonus/equity: eli...
Mlops engineering leadership
Cloud-native data pipelines
Multimodal sensor data processing
This role offers an outstanding opportunity to lead the build, development, and operation of large‑scale, end‑to‑end data and ML pipelines that power NVIDIA’s autonomous driving products

Job Summary

  • This role offers an outstanding opportunity to lead the build, development, and operation of large‑scale, end‑to‑end data and ML pipelines that power NVIDIA’s autonomous driving products.
  • You will lead a highly technical engineering team responsible for building and operating cloud‑scale pipelines that ingest, validate, process, and transform extensive volumes of multimodal sensor data into high‑quality training, evaluation, and validation datasets.
  • NVIDIA is widely considered one of the most sought-after employers in the technology industry and offers highly competitive compensation along with an extensive benefits plan.

Matching Summary

This role offers an outstanding opportunity to lead the build, development, and operation of large‑scale, end‑to‑end data and ML pipelines that power NVIDIA’s autonomous driving products.

Salary

Base: 272,000 USD - 431,250 USD; Bonus/Equity: Eligible for equity; Benefits: Extensive benefits plan

Skills & Requirements

Must-have

  • MLOps engineering leadership
  • cloud-native data pipelines
  • multimodal sensor data processing
  • Python and C++ proficiency
  • large-scale distributed systems
  • end-to-end ML pipelines
  • autonomous driving technology

Nice-to-have

  • AV-scale data platform experience
  • workflow orchestration expertise
  • 3D geometry and perception pipelines
  • customer-focused engineering
  • mentorship and career development
  • cross-functional collaboration
  • production MLOps infrastructure

Key Requirements

  • 10+ years engineering experience
  • 5+ years engineering management
  • Bachelor’s or higher in CS or related field
  • experience with production distributed systems
  • strong background in MLOps and data pipelines
  • excellent communication and leadership skills

Work Rights

Not specified

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