Offer summary

Qualifications:

Bachelor’s Degree in a technical field, Proficiency in Python scripting, Experience with SQL and automation, Familiarity with cloud platforms (AWS, GCP, Azure), Experience with data annotation platforms.

Key responsabilities:

Build and maintain Python scripts to streamline annotation

Optimize data labeling pipeline for efficiency

Collaborate with QA to ensure data quality

Integrate third-party tools with Labelbox

Provide technical support to project managers and labelers

Job description

Labelbox is the data factory for generative AI, providing the highest quality training data for frontier and task-specific models. Labelbox’s comprehensive platform combines on-demand labeling services with the industry-leading data labeling platform. The Boost labeling service is powered by the Alignerr community of highly-educated experts, who span all major languages and a diverse range of advanced subjects. They are available on-demand to rapidly generate new data for supervised fine-tuning, RLHF, and more. Labelbox’s software-first approach delivers unmatched control and transparency into the labeling process, leading to the generation of high-quality, consistent data at scale.

Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs.

About the Role

We are seeking a skilled and detail-oriented Data Operations Engineer to support our data annotation production processes. In this role, you will play a critical part in optimizing, maintaining, and scaling our data labeling workflows, primarily using Labelbox. You will ensure that labelers are able to efficiently and accurately generate data by building tools, automating tasks, and troubleshooting complex issues within the production pipeline. Your ability to script in Python and apply engineering principles to data operations will be key to improving both efficiency and quality across our projects.

Your Day to Day

Build, deploy, and maintain Python scripts and other tools to streamline the data annotation process, automate repetitive tasks, and reduce manual effort.
Identify bottlenecks in the data labeling pipeline and implement solutions to enhance throughput, accuracy, and scalability of labeling operations.
Work closely with the quality assurance team to ensure that data labeling meets accuracy standards and troubleshoot any issues related to data quality.
Integrate and manage third-party tools with Labelbox, ensuring seamless operation and data flow across platforms.
Provide ongoing technical support to the project managers and labelers, assisting with technical challenges in Labelbox and associated tools.
Set up monitoring tools to track the performance of data annotation operations, reporting key metrics and areas for improvement to leadership.

About You

Bachelor’s Degree in Engineering, Computer Science, Data Science, or a technical field.
Proficiency in Python scripting and experience with automation of operational tasks.
Proficiency in SQL.
Experience with Labelbox or similar data annotation platforms.
Strong analytical and problem-solving skills with a demonstrated ability to optimize processes.
Experience with data pipelines and data workflow management.
Familiarity with cloud platforms such as AWS, GCP, or Azure.
English fluency.

Nice to Have

Prior experience in a production or process engineering role, especially in data operations or similar environments.
Knowledge of machine learning workflows and the data requirements for AI training.
Understanding of project management methodologies and the ability to work collaboratively across teams.

Labelbox strives to ensure pay parity across the organization and discuss compensation transparently. The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.

Annual base salary range

$70,000—$90,000 USD

Excel in a remote-friendly hybrid model.

We are dedicated to achieving excellence and recognize the importance of bringing our talented team together. While we continue to embrace remote work, we have transitioned to a hybrid model with a focus on nurturing collaboration and connection within our dedicated tech hubs in the San Francisco Bay Area, New York City Metro Area, and Wrocław, Poland. We encourage asynchronous communication, autonomy, and ownership of tasks, with the added convenience of hub-based gatherings.

Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice.

Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.

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