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Engineering Manager, Data Labeling Platform

NVIDIA· Mgmt, SW Eng
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Hybrid (Remote / US)$200k - $391kFull-timePosted 1mo ago

About the role

Engineering Manager to lead, scale, and innovate NVIDIA's core Data Labeling Platform, bridging AI engineering, scalable software systems, and large-scale operations. Lead a team designing next-generation data annotation platform supporting high-volume annotation projects across multiple domains with an emphasis on operational efficiency, models-in-the-loop, auto-labeling, data pipelines, and intelligent orchestration.

Responsibilities

  • System Design & Programming: Guide robust software design, maintain a high technical bar, and contribute Python programming when solving architectural bottlenecks.
  • People Leadership: Build, mentor, and lead a high-performing team of software, data, and AI application engineers; foster technical excellence and growth.
  • Stakeholder Management: Align engineering roadmaps with VPs, Research Leaders, and Data Factory operations workforce.
  • AI Application Engineering: Architect and drive auto-labeling applications leveraging multi-modal models-in-the-loop to reduce human labeling latency.
  • Data Engineering & Analytics: Own data engineering layer, event logging, ETL into NVIDIA's data lake, metrics, dashboards, and alerting against reliability/latency targets.
  • Front-End & Annotation Interfaces: Direct front-end engineering for custom annotation interfaces across modalities to optimize annotator throughput and error rate.
  • Operations Scaling: Optimize platform for scalability, data integrity, and throughput; ensure seamless interaction between annotators and ML systems.

Qualifications

  • Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or related field (or equivalent experience).
  • 10+ years of professional software engineering experience, including 2+ years as a technical lead or engineering manager
  • Hands-on Engineering: strong background as Software Engineer, Data Engineer, or AI Application Engineer; strong system design and Python experience.
  • AI & Data Engineering: architecture-level understanding of data pipelines, distributed systems, and production ML workflows (auto-labeling or human-in-the-loop).
  • Leadership Capability: experience leading technical initiatives, mentoring engineers, or formally managing a team; senior ICs with tech-lead experience considered.
  • Exceptional Communication: ability to manage stakeholders and translate technical constraints for VPs and operational teams.

Skills

Required:PythonSystem DesignLeadership

Benefits

  • Equity
  • Benefits (as listed in company benefits page)
Last updated Oct 9, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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