Data Operations Engineer

Job Description

Labelbox is seeking a Data Operations Engineer to enhance data annotation and quality assurance processes. The successful candidate will play a crucial role in optimizing and scaling data labeling workflows using Labelbox. This role involves building tools, leveraging LLM models, automating project management tasks, and troubleshooting production pipeline issues.

Responsibilities:

• Build, deploy, and maintain Python automation scripts.
• Identify and resolve bottlenecks in the data labeling pipeline.
• Collaborate with the Project Management team to ensure data meets accuracy standards.
• Plan quality assurance workflows for data anomaly detection.
• Set up monitoring tools to track performance and report key metrics.
• Integrate and manage third-party API tools with Labelbox.
• Provide technical support to project managers and labelers.

Requirements:

• 3+ years of experience in a technical role.
• Bachelor’s Degree in Engineering, Computer Science, or a technical field.
• Proficiency in Python scripting and automation.
• Experience with Labelbox or similar platforms.
• Strong analytical and problem-solving skills.
• Experience with data pipelines and workflow management.
• Familiarity with cloud platforms (AWS, GCP, or Azure).
• English fluency.

Labelbox Offers:

• Hybrid work style with 2 days per week in the office.
• Career advancement opportunities.