Über
Responsibilities
Designing, building, and optimizing machine learning models for production use, with a focus on recommender systems.
Develop and maintain scalable ML pipelines, including data processing, training, evaluation, and deployment.
Work with large datasets to extract insights and improve model performance.
Collaborate with cross-functional teams to integrate ML solutions into production systems.
Continuously improve model performance through experimentation, tuning, and monitoring.
Ensure reliability and scalability of ML systems in cloud environments.
Qualifications
5+ years of hands‑on experience in machine learning engineering
Strong proficiency in Python and core ML frameworks (e.g., PyTorch, TensorFlow, scikit‑learn, XGBoost, etc.)
Solid experience with deep learning, including model architecture, training, and optimization
Proven experience designing and deploying recommender systems
Hands‑on experience with AWS SageMaker and the broader AWS ML ecosystem
Practical experience building and maintaining data pipelines and ML workflows
Experience working with production ML systems and MLOps practices
What We Offer
Fully remote work
International team with clear processes
Paid vacation, holidays, and sick leave
Apply Now Send us your CV and we will get back to you.
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Sprachkenntnisse
- English
Hinweis für Nutzer
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