Machine Learning Data Engineer

Smartex.Ai; Porto; Presencial; EUR 55 000 - 85 000; Tempo integral

Resumo da oferta

Smartex.Ai in Porto is seeking a Machine Learning Data Engineer to build and improve data systems supporting inspection products, from Python backend services and processing pipelines to dashboards. You will work closely with the Head of Data and ML team to understand data flows from collection through labeling to model use, and help improve data operations and tooling.

Fluent English required; 4+ years of data engineering or related software experience, with strong Python skills and data

Qualificações

• 4+ years of professional data engineering or related software experience.
• Strong Python backend development and data-processing tooling.
• Experience with building and maintaining data pipelines and dashboards.

Responsabilidades

• Build and maintain data pipelines for collection, labeling, processing and dataset preparation.
• Develop Python backend services, APIs, and internal tools to improve data workflows.
• Create dashboards and reports to monitor dataset coverage, labeling progress, and quality.

Conhecimentos

Python

SQL

Data modeling

Git

Ferramentas

SQL databases

Git

Docker

Descrição da oferta de emprego

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

Machine Learning 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. 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. +4 Professional experience in data engineering, Python backend development, or a related software role. Strong practical Python skills, including building and maintaining services, automation, or data-processing tools. Confidence with SQL, relational databases, and data modeling.

Experience developing data pipelines and handling incomplete, inconsistent, or changing data. Experience building dashboards or reports that help teams monitor performance and make decisions. Demonstrated ability to coordinate work across colleagues, mentor others, and help a team deliver, with sound judgment and a sense of ownership. Ability to break an unclear problem into actionable work, set priorities, and follow through on delivery. Experience with Git and good software development practices, including testing and documentation. Clear communication with technical and non-technical colleagues, and fluency in English.

Nice to Have

Direct experience managing a data, engineering, or labeling team, including onboarding and performance feedback. Familiarity with data annotation, dataset quality checks, or workflows supporting machine learning. Experience with cloud platforms, workflow orchestration, or monitoring data pipelines in production. Experience in textiles, manufacturing, or industrial data, and an interest in learning how woven fabrics are inspected.

Machine Learning Data Engineer Porto, Portuguese Republic, PT