Data Engineer, Image Recognition - (Quick Commerce) at Delivery Hero

Barcelona, Catalonia, Spain -

Full Time

Start Date

Immediate

Expiry Date

27 May, 26

Salary

0.0

Posted On

27 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, ETL/ELT Pipelines, Data Validation, Feature Pipelines, Model Training, Image Recognition, Computer Vision, ML Model Deployment, CI/CD Pipelines, Observability, Monitoring, A/B Testing, Cloud Platforms, Docker, Kubernetes

Industry

technology;Information and Internet

Description

Company Description As part of the Delivery Hero Group, Glovo is the fastest-growing multi-category app in Spain, connecting millions of users with businesses, and couriers, offering on-demand services from more than 170,000 local restaurants, grocers and supermarkets, and high street retail stores, operating in more than 1500 cities across 25 countries. We are proud to make a significant and valuable contribution to the strategic positioning of the Delivery Hero Group on the global market through our unique expertise. Job Description About the opportunity We are on the lookout for a Data Engineer to join our Quick Commerce team on our journey to always deliver amazing experiences. Be part of redefining how customers experience quick commerce. You’ll help build technology that scales our non-food offerings, reaching new market segments and driving revenue growth. By innovating within our Quick Commerce Team, you’ll make Delivery Hero the go-to platform for a broad range of products, helping us grow faster and deliver more value to customers around the world. We are building the AI engine that helps vendors upload and update their catalog on our platform in the easiest and quickest way possible. As a Data Engineer, you will work side-by-side with a Data Scientist and Software Engineers to design, build, and deploy ML models that automate content creation and power a smarter product assortment. We need a Data Engineer, but someone who is interested in transitioning to an MLE role in the future, once the product is more mature. This means this is a role for someone who has a strong background in applied ML, and is hungry to build a reliable and scalable image recognition system. If you’re a strong coder with a problem-solving mentality and thrive in high-scale applied ML problems, we’d love to talk. THE JOURNEY Design and build resilient ETL/ELT pipelines to ingest, clean, and validate image data and associated metadata (e.g., vendor catalog features). Work with the Data Scientist to create and maintain the "Ground Truth" dataset (human-validated, accurately labeled data) necessary for calibrating the third-party model and benchmarking the accuracy. Build reliable, production-grade feature pipelines to ensure that data used during model training is identical to the data used during live inference (avoiding training/serving skew). Build the automated infrastructure to support the Data Scientist's model training cycles, focusing on data versioning and reproducibility. Contribute to the long-term vision of products image recognition, while delivering short-term wins that unlock measurable business impact. Qualifications WHAT YOU WILL BRING TO THE RIDE Bachelor's degree in computer science, information systems, mathematics, statistics, or a related field. 3+ years of professional experience as a Data Engineer or Machine Learning Engineer. Advanced knowledge of SQL and distributed processing frameworks. Excellent engineering skills: write clean, maintainable Python code. Strong systems-level problem-solving skills, with the ability to balance performance, scalability, maintainability, and business impact. Excellent communication skills, with the ability to clearly articulate complex technical problems and solutions to both engineers and business stakeholders. Nice to have: PhD in AI, Machine Learning, or a related field. Experience on Computer Vision (CV). Excellent engineering skills: Experience bringing ML models into production with best practices for observability, monitoring, and performance. Experience with CI/CD pipelines and commonly used tools in ML Engineering such as Metaflow, MLflow, Airflow, Grafana, and similar. Experience with large-scale ML model validation, experimentation, and A/B testing. Hands-on experience with major cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes). Additional Information Individuals representing diverse profiles, and abilities, encompassing various genders, ethnicities, and backgrounds, are less likely to apply for this role if they do not possess solid experience in 100% of these areas. Even if it seems you don't meet our musts don't let it stop you, we are all about finding the best talent out there! Skills can be learned, and embracing diversity is invaluable. We believe driven talent deserves: 🍔 Monthly Glovo credits to satisfy your cravings! 🏊 Discounted gym memberships to keep you energized. 🏖️ Extra time off, the freedom to work from home two days a week, and the opportunity to work from anywhere for up to three weeks a year! 👪 Enhanced parental leave, and office-based nursery. 🧠 Online therapy and wellbeing benefits to ensure your mental well-being. Here at Glovo, we thrive on diversity, we believe it enhances our teams, products, and culture. We know that the best ideas come from a mashup of brilliant diverse minds. This is why we are committed to providing equal opportunities to talent from all backgrounds - all genders, racial/diverse backgrounds, abilities, ages, sexual orientations and all other unique characteristics that make you YOU. We will encourage you to bring your authentic self to work, fostering an inclusive environment where everyone feels heard. Feel free to note your pronouns in your application (e.g., she/her/hers, he/him/his, they/them/theirs, etc). So, ready to take the wheel and make this the ride of your life? Delve into our culture by taking a peek at our Instagram and check out our Linkedin and website! Here at Glovo, we thrive on diversity, we believe it enhances our teams, products, and culture. We know that the best ideas come from a mashup of brilliant diverse minds. This is why we are committed to providing equal opportunities to talent from all backgrounds – all genders, racial/diverse backgrounds, abilities, ages, sexual orientations and all other unique characteristics that make you YOU. We will encourage you to bring your authentic self to work, fostering an inclusive environment where everyone feels heard. Feel free to note your pronouns in your application (e.g., she/her/hers, he/him/his, they/them/theirs, etc). So, ready to take the wheel and make this the ride of your life? Delve into our culture by taking a peek at our Instagram and check out our Linkedin and website!

Responsibilities

The role involves designing and building resilient ETL/ELT pipelines to process image data and metadata, and creating production-grade feature pipelines to ensure consistency between model training and live inference data. The engineer will also build infrastructure to support model training cycles, focusing on versioning and reproducibility.