Engineering Manager, Data Labeling Platform

Details

NVIDIA is seeking an Engineering Manager to lead, scale, and innovate its core Data Labeling Platform. The role bridges AI engineering, scalable software systems, and large-scale data operations. The team builds software supporting high-volume annotation projects across research areas including Nemotron, Cosmos, Robotics, and red teaming, using internal data operations and external annotation partners.

Responsibilities

• Lead a team of software, data, and AI application engineers.
• Maintain a high technical bar through robust system design, clean data engineering practices, and occasional hands-on Python programming.
• Build, mentor, and manage a high-performing engineering team.
• Align engineering roadmaps with VPs, research leaders, and the Data Factory operations workforce.
• Architect and implement auto-labeling applications using multimodal models-in-the-loop to reduce human labeling latency.
• Own the data engineering layer for annotation measurement, including event logging, ETL into NVIDIA's data lake, metrics, dashboards, and alerting against reliability and latency targets.
• Direct front-end engineering for custom annotation interfaces covering text, video, audio, speech, and document modalities.
• Optimize the platform for scalability, data integrity, and throughput while improving the interface between human annotators and machine learning systems.

Requirements

• Bachelor's, Master's, or PhD in Computer Science, Engineering, or a related technical field, or equivalent experience.
• 10+ years of professional software engineering experience, including 2+ years as a technical lead or engineering manager.
• Strong background as a software engineer, data engineer, or AI application engineer.
• Excellent system design skills and deep hands-on expertise in Python.
• Architecture-level understanding of data pipelines and distributed systems.
• Experience integrating machine learning models into production workflows, particularly auto-labeling or human-in-the-loop systems.
• Experience leading technical initiatives, mentoring engineers, or formally managing a team.
• Exceptional stakeholder management and communication skills, including communicating technical constraints to VPs and translating business goals into operational directives.

Preferred Qualifications

• Experience with human-in-the-loop data programs, including RLHF, preference data, red teaming, test datasets, vision datasets, or multimodal datasets.
• Experience applying models to reduce or assist human effort in labeling workflows, such as automated pre-labeling, model-based quality evaluation, or agent-driven internal tooling.
• Working proficiency in TypeScript or JavaScript.
• Experience delivering applications where interaction design affects user throughput and error rates.
• Experience with multimodal data, including video, 3D and point clouds, speech, or document understanding.

Compensation and Benefits

The base salary range is USD 200,000–322,000 for Level 3 and USD 248,000–391,000 for Level 4. Compensation depends on location, experience, and pay for employees in similar positions. The role also includes eligibility for equity and benefits.