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We are a technology consultancy working with enterprise B2B clients across the US and Europe — manufacturing, distribution, high-tech. Our teams build and integrate complex digital commerce solutions on platforms like SAP, Salesforce, and Shopify. The project is long-term and actively growing.
Job Responsibility:
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
Requirements:
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