What we're looking for
The Machine Learning Team at Smartex is committed to revolutionizing the textile industry through the development of cutting-edge AI solutions. We are a diverse and international company with a strong mission to make a positive impact on both our industry and the planet.
We are looking for a driven Data Engineer to build and improve the data systems that support our inspection products, from Python backend services and processing pipelines to dashboards. You will work closely with our Head of Data and Machine Learning team to understand how data moves from collection through labeling to use in our models.
Alongside building software, you will learn our data operations through close collaboration with the team and help improve how work is organized and delivered. Your focus will be building reliable data systems and improving data quality. Experience with neural networks, computer vision, or image processing is not required.
Responsibilities
- Build and maintain pipelines for collecting, validating, processing, and organizing data used by our Machine Learning team.
- Develop Python backend services, APIs, and internal tools that improve data collection, labeling, review, and dataset preparation.
- Create dashboards and reports that make dataset coverage, labeling progress, quality, and operational bottlenecks visible to the team.
- Translate product and ML requirements into practical data workflows, coordinate dependencies with colleagues, and follow through on delivery.
- Work with ML engineers and textile experts to define and maintain woven defect categories and labeling guidelines, then translate them into usable data workflows.
- Work alongside the data and labeling team to understand operational challenges, improve tools and guidelines, and support colleagues in using them.
- Collaborate with the Head of Data on planning and process improvements, building a practical understanding of the team's workflows and quality standards.
- Document processes and maintain tested, readable code so knowledge and ownership are shared across the team.
Contact
Rita Santos, Director of People.
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