Machine Learning Engineer
Shalion Barcelona, Catalonia, Spain
IT Services and IT Consulting · 51-200 employees
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About the role
Own the lifecycle of machine learning systems, focusing on deployment, monitoring, and converting existing models and notebooks into modular, tested production code. Improve engineering practices and CI/CD workflows, collaborate with Data Scientists and Data Engineers on reliable interfaces and data flows, and provide technical guidance through code reviews.
What they look for
Requirements
Candidates should have experience building and deploying machine learning systems in production, strong Python software engineering skills, and a proven ability to move models from notebooks into production. A solid understanding of the model development lifecycle is expected; Docker, AWS, and Snowflake experience are bonuses.
Benefits
Full description
About us
Shalion is a data and insights-driven company that serves world-class manufacturers and brands globally. Through our Digital Shelf Optimization, Retail Media, and Food Service Aggregators solutions, we provide innovative tools for e-commerce monitoring.
At Shalion, we empower brands to make smarter business decisions in eCommerce by delivering actionable data and insights on online product prices, availability, share of search, and more. We operate across 1000+ e-retailers in 60+ countries, serving industry giants such as Heineken, Lego, Danone, Nestlé, and JDE.
As a leader in data intelligence, we specialize in gathering, analyzing, and applying proprietary artificial intelligence to deliver relevant data and monitoring tools, helping our clients maximize their e-commerce performance.
The role
As a Machine Learning Engineer, you will join our Data Science team and play a key role in transforming research-driven work into robust, production-ready systems. You will help elevate the team’s engineering maturity, promote best practices, and ensure that models are scalable, maintainable, and deliver real business impact.
Your Responsibilities:
- Own the end-to-end lifecycle of ML systems, with focus on deployment and monitoring.
- Refactor and productionize existing models and notebooks into clean, modular, and testable code.
- Introduce and enforce best practices in coding, testing, model versioning
- Set up and improve CI/CD workflows for ML systems.
- Work closely with Data Scientists and Data Engineers to ensure clean interfaces and reliable data flows
- Act as a technical reference within the team, reviewing code and guiding less experienced members.
Your profile:
- Experience building and deploying ML systems in production environments
- Strong software engineering skills in Python, with a focus on writing clean, maintainable, and testable code
- Proven experience taking models from notebook to production
- Solid understanding of model development lifecycle
- (Bonus) Familiarity with containerization (Docker)
- (Bonus) Experience with cloud environments (AWS preferred) and data platforms such as Snowflake
Soft Skills:
- Pragmatic and solution-oriented: you focus on what works in production, not just in theory
- Comfortable working in ambiguous environments and bringing structure where needed
- Quality-driven mindset with attention to maintainability and long-term scalability
Interview process:
- First interview: Intro & mutual fit
- Second interview: Technical discussion
- Third interview: Deep dive with Tech Lead
What we offer you
- 🌍 An international team – Work with colleagues from 10+ nationalities.
- 🚀 A dynamic and innovative environment – Be part of a high-performing team.
- 🏢 Hybrid work model – 3 days in-office, 2 days remote.
- 💡 Impactful work – Contribute to a challenging and innovative project.
- 🎟 Flexible benefits – allocate part of your gross salary (pre-tax) to meal vouchers, transport allowance, and private healthcare at a preferential rate.
- 🍏 Office perks – Fresh fruit and specialty coffee daily.
- 📄 Contract: Permanent
- 📍 Great location – Office in Barcelona’s Sarrià-Sant Gervasi district.
Shalion Data Services Limited is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
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