ML Engineer in the EU

Quick Facts

• Role: ML Engineer (EU)

Description

The role focuses on designing, training, and evaluating scalable machine learning models, building scalable data and ML pipelines, and deploying production-ready AI solutions. You will work across the ML lifecycle—from preparing training datasets and developing/evaluating models to deploying models for batch or real-time inference and monitoring performance and data quality.

Responsibilities

• Design, train, and evaluate machine learning models (supervised, unsupervised, NLP, etc.)
• Build scalable data and ML pipelines using modern tools
• Collaborate with subject matter experts and analysts to prepare training datasets
• Deploy models for production (batch or real-time inference)
• Monitor and maintain model performance and data quality
• Optimize models for performance, interpretability, and cost
• Document ML workflows and ensure reproducibility

Requirements

• Experience as a Machine Learning Engineer or in a similar role for 2+ years
• Proficiency in Python, including hands-on experience with scikit-learn, pandas, NumPy, and matplotlib
• Strong understanding of core ML concepts: regression, classification, clustering, model validation, and performance metrics
• Practical experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras
• Proven experience building, training, and deploying ML models using AWS SageMaker
• Familiarity with AWS Bedrock for working with foundation and generative models (fine-tuning and orchestration of LLMs)
• Hands-on experience with data preprocessing, feature engineering, and model evaluation
• Knowledge of SQL and experience working with structured and semi-structured datasets
• Understanding of ML model deployment (REST APIs with FastAPI or Flask; model packaging and containerization with Docker)
• Exposure to MLOps practices: pipeline automation, model versioning, monitoring, and reproducibility
• Familiarity with version control systems (Git)
• Strong analytical thinking, communication, and problem-solving skills
• Willingness to stay current with emerging ML techniques, frameworks, and cloud AI tools
• English: Upper-Intermediate+
• German: Intermediate+

Benefits

• Fully remote, office, or hybrid options
• Professional, financial, and career growth with mentoring and adaptation for new employees
• Up to an additional $1,000/month in annual bonus based on expertise
• Access to a corporate training portal
• Corporate life (parties, pizza days, PlayStation, fruits, coffee/snacks, movies)
• Certification compensation (AWS, PMP, etc.)
• Referral program
• English courses
• Private health insurance and compensation for sports activities