Data Engineer (I)

Overview

Aquent is partnering with a leading technology company that stands at the forefront of innovation, continuously shaping how people interact with information and the world. This organization is dedicated to pushing boundaries and creating impactful solutions that touch millions globally. Join their dynamic team and play a pivotal role in ensuring the integrity and usability of critical data that underpins groundbreaking research and advanced model development, directly influencing the future of technology.

About the Role

Step into a vital role where your expertise will directly influence the quality and accessibility of data for cutting-edge research and development. As a Data Engineer, you will be instrumental in building robust data pipelines, refining raw datasets, and creating essential tools that empower researchers and engineers to innovate faster and more effectively. Your contributions will directly enable the development and evaluation of next-generation AI models, making a tangible impact on future technological advancements.

Key Responsibilities

• Design and implement agentic data processing pipelines for comprehensive data analysis, visualization, and debugging.
• Ensure high data quality by meticulously cleaning, structuring, and cataloging raw spatial and research datasets.
• Collaborate closely with researchers to deliver processed data outputs that meet their specific project requirements.
• Coordinate with a remote team to manage task expectations, oversee annotation job queues, analyze annotation quality, and provide constructive feedback to rating teams.

Required Skills & Experience

• Proven programming proficiency in Python, with a strong background in developing tools, web UIs, and scripts for data collection, annotation, and processing.
• Demonstrated data science and engineering capabilities, including expertise in data quality verification, building agentic data processing pipelines, data visualization, and comprehensive data analysis.
• Experience in designing and conducting human studies or surveys to gather valuable insights.
• Exceptional communication skills, enabling effective technical discussions with researchers and software engineers, as well as clear communication regarding data annotation with non-technical raters.

Nice-to-Have Skills

• Familiarity with VLM (Vision-Language Model) evaluation methodologies.
• Experience with the evaluation of multi-modal Generative AI models, such as image generation and video generation.