Data Operations Specialist – GenAI Annotation

Sustainable Talent is partnering with NVIDIA , a global leader in AI and accelerated computing, to hire a Data Operations Specialist – GenAI Annotation to support the Annotation Project Design Team responsible for enabling high-quality training data at scale for foundational models.

This is a W-2 full-time contract role that is fully remote within the U.S. Preferred location is in or near Santa Clara, CA (hybrid welcome), with strong preference for Pacific Time. We offer a competitive pay range of $40–$60/hr , based on experience and location, along with full benefits, PTO, and excellent company culture. NVIDIA is seeking a dynamic and versatile Data Operations Specialist – GenAI Annotationto design and optimize annotation workflows that support model training and evaluation.

You will work across teams to automate pipelines, configure tools, and support multi-stage, model-in-the-loop workflows essential to LLM development.

What You’ll Do

• 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.

What We’re Looking For

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

Sustainable Talent is a M/F+, disabled, and veteran equal employment opportunity and affirmative action employer.

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Do you have 3-6 years of experience in AI/ML operations, data/product operations, or software development?
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Python scripting for automation

Python scripting for data processing

Python scripting for integrating with telemetry and monitoring systems

Have you worked with any data annotation platforms (e.g., Labelbox, Scale AI, Super Annotate, Snorkel, or internal tools)- check all that apply: *

Labelbox

Super Annotate

Snorkel

Do you have hands-on experience with structured data formats like CSV, JSON, or JSONL?
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Have you worked with cloud storage systems such as AWS S3, GCS, or Azure Blob for dataset management or pipeline workflows?
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