Data Annotation Engineer

Summary

Join NVIDIA as a GenAI Annotation Operations Engineer and contribute to high-quality training data for foundational models. This full-time, fully remote (U.S.) contract role involves designing and optimizing annotation workflows, automating pipelines, and supporting model-in-the-loop processes. You will collaborate with various teams, troubleshoot issues, and document workflows. The ideal candidate possesses 2–5 years of experience in data annotation operations or software/data engineering, proficiency in Python scripting, and experience with annotation tooling. A competitive hourly rate ($40–$60/hr) is offered, along with full benefits and PTO. Preference is given to candidates located near Santa Clara, CA, with a hybrid work option available.

Requirements

• 2–5 years of experience in data annotation operations, ML data workflows, or software/data engineering
• Proficiency in Python scripting for automation and data handling (JSON, JSONL, CSV)
• Comfort working with AWS S3 and cloud-based storage pipelines
• Strong communication skills to interface with technical and non-technical stakeholders
• Experience in multi-stage annotation workflows or model-in-the-loop systems

Responsibilities

• Set up, test, and maintain UI configurations for annotation tasks using third-party and internal platforms
• Build and adapt Python-based automation scripts for annotation pipelines, data processing, logging, and telemetry
• Collaborate with researchers, engineers, PMs, and annotators to gather requirements and design workflows
• Own projects end-to-end — from requirement gathering through delivery of annotated datasets
• Track progress, manage risks, and implement corrective actions to keep workflows on track
• Troubleshoot issues related to UI, pipelines, and data formatting
• Document workflows and contribute to internal tools, playbooks, and pipeline validation logic
• Support annotation operations across varied data types — with focus on LLMs and GenAI training

Preferred Qualifications

• Experience with annotation tooling (e.g., Scale AI, Labelbox, SuperAnnotate) is highly preferred
• Bonus: familiarity with telemetry systems, GenAI/LLM training environments, or RLHF pipelines

Benefits

• Full benefits
• PTO