Senior Machine Learning Engineer (Personalization)

Quick Facts

• Role: Senior Machine Learning Engineer (Personalization)

• Focus: campaign ranking, product recommender optimization, and churn prevention via smart communication models

• Work model: hybrid or fully remote (with some in-office days)

Description

You will own business-critical machine learning logic for a campaign-based flash sale model, driving how campaigns are ranked based on customer interests and category affinities. You’ll optimize product recommender systems and help prevent churn using smart communication models. The role includes end-to-end ML ownership and close collaboration with product, data, and development teams.

Responsibilities

• Build and deploy data-driven ML solutions for portal personalization and campaign ranking

• Own the end-to-end ML process (data quality checks, algorithm selection, feature engineering, validation with correct metrics, and interpretability)

• Monitor, maintain, scale, and update existing data/ML pipelines

• Implement solutions following best software practices (clean code, testing, automatic deployments)

• Collaborate with data engineers and developers to build ML/data infrastructure with reliable pipelines and clean shared data sources

• Explain and recommend ML approaches to business stakeholders and engineering teams

• Share and improve ML/MLOps knowledge across the organization

Requirements

• 3–5+ years of professional experience building, training, validating, and deploying ML solutions in production

• Very good knowledge of Python, SQL, and Git

• Experience training and validating ML solutions (decision trees, neural nets, regression models)

• Ability to scale solutions according to infrastructure or business needs

• Good understanding of data lake/lakehouse architecture

• Good English knowledge (C1)

Benefits

• Hybrid or remote work model with flexible start times

• Wellbeing platform, private medical care, and a Multisport card

• Learning & development through courses, podcasts, language learning, and international projects

• Office perks and activities (wellness and social events)

• Eco-focused initiatives