Data Quality Engineer

You will:

• Oversee, plan, and take care of data collection and labeling projects. Keep an eye out for automation opportunities to make things easier over time
• Build and keep up solid relationships with our outside vendors and contractors: ensure our collaboration is smooth and valuable
• Create labeling instructions and evaluate data quality. Make sure we’ve got a good mix of quality, diversity, and quantity of data. Brainstorm ways to make our tools or instructions more user-friendly.
• Keep tabs on ongoing projects to make sure we’re putting our resources in the right places. Be ready to tweak project scope and instructions when new information comes in.
• Share updates on projects, including by building diagnostics/dashboards and data analysis tools/reports.
• Work hand in hand with the rest of the Engineering org to make our interfaces (both code interfaces and human interfaces) even better.

You should have:

• Strong professional english speaking and writing skills
• 3+ years of software development or analytics-heavy operations experience
• 2+ years of experience with Python or other popular industry tools for automation
• Enjoy paying attention to details and analyzing information and data
• Have excellent project management skills, and can work with internal and external teams
• Understand the workings of LLMs or VLMs and prompt engineering
• Have experience in gathering, labeling, and analyzing data
• Agree that data is the key ingredient for the performance of AI models

You may be a good fit if you have:

• Have worked with data collection and labeling for multimodal language models
• Have managed a team of external contractors or vendors.
• Have launched new technical programs.
• Have worked with research scientists and engineers.

Relevant Tech Stack

• Python (pandas, Jupyter, etc.), and SQL
• Visualization tools (any popular frameworks)
• Project management tools such as Jira, Confluence, etc.