Machine Learning Engineer

One Matching connects offers from thousands of shops to the right products in our catalogue across Heurekas marketplaces. We build and run the systems that do it at the scale of millions of offers.

For us an ML engineer works across four areas: software engineering model training evaluation and data analysis. You dont need to be the best at all four but you should be able to move between them.

• Own problems end to end from understanding the business need to measuring the result in production.
• Build and improve ranking matching and data-quality systems using both classic ML and LLMs.
• Work with content and product teams to turn vague business problems into concrete technical plans and explain the trade-offs.
• Help decisions along by proposing a direction and working with the team to reach a solution.
• Think about the whole system from search and features through models thresholds and deployment and the services that depend on them.

• You think business-first and weigh effort against value.
• Applied ML experience: training and evaluating classic models (XGBoost scikit-learn) calibration error analysis and knowing when not to use ML.
• Hands-on MLOps from deploying models to monitoring and maintaining them in production.
• Solid software engineering including reliable production Python you own end to end. Cloud experience ideally GCP.
• You can scope work sequence it and estimate it realistically.
• Enough ownership to decide with incomplete information and correct course as you learn.
• Clear communication with engineers and non-technical stakeholders.

• LLMs in production (annotation evaluation extraction)
• Elasticsearch or similar
• Vertex AI our ML pipeline platform
• E-commerce experience

Python GCP Elasticsearch XGBoost classic ML and LLMs. LLMs are in production today and we are moving toward agent-based development.

We are a small team so you get a lot of say in what you work on and how you do it. You will not be doing it alone. We plan together review each others designs and help each other get things into production. We keep solutions as simple as the problem allows.

• Impact: Your code shapes the shopping experience for millions of people.
• Hackathons & conferences: We support your participation in events like DevFest or devopsdays.
• Flexibility: Home office up to 3 days a week and flexible hours. We meet in the office at least once every two weeks for team collaboration and scrum ceremonies.
• Career journey: A clear roadmap to help you grow.
• The basics: 25 days of vacation extra time off a Cafeteria benefit system and a Multisport card.