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Senior ML Engineer

2 hours, 5 minutes ago
Albania, North Macedonia, Poland, Romania, Ukraine, Turkey
Full-time
Senior
Machine Learning Engineer
Software Development
AWS Deep Learning Machine Learning MLOps Neural Networks Python PyTorch SageMaker Scikit-learn SQL TensorFlow XGBoost
Apply Now
Symphony Solutions

Symphony Solutions

Symphony Solutions is a Cloud and Agile transformation company headquartered in the Netherlands, with delivery centers in Ukraine, Poland, Macedonia, and The Netherlands. Founded in 2008, the company is now 600 people with over 35 international clients...

Internet Software & Services
251-1K
Founded 2008
View All Jobs 8

Description

  • Design, train, and iterate on machine learning and deep learning models for recommendation, ranking, and personalization use cases.
  • Architect and maintain end-to-end machine learning pipelines on AWS.
  • Set up and optimize data processing and machine learning workflows using AWS services.
  • Build and maintain MLOps infrastructure for production ML systems.
  • Collaborate with data engineers to ensure data quality, build feature stores, and prepare training and inference datasets.
  • Evaluate and benchmark model performance using offline and online experiments to improve accuracy and efficiency.
  • Optimize model serving infrastructure for latency, throughput, and cost-effectiveness.
  • Partner with product and business stakeholders to translate requirements into well-scoped machine learning solutions.
  • Document model architecture, assumptions, performance characteristics, and known limitations.
  • Stay current with advances in recommendation systems, deep learning, and cloud ML services and propose improvements to existing approaches.

Requirements

  • 4+ years of hands-on experience in machine learning engineering.
  • Strong proficiency in Python and core ML frameworks such as PyTorch, TensorFlow, scikit-learn, and XGBoost.
  • Solid experience with deep learning, including architecture design, training, hyperparameter tuning, and deployment of neural network models.
  • Proven experience designing and deploying recommender systems.
  • Hands-on experience with AWS SageMaker and the broader AWS ML ecosystem.
  • Practical experience setting up data processing and ML workflows on AWS.
  • Strong MLOps skills and solid understanding of the full ML lifecycle.
  • Hands-on experience with containerization and orchestration in production environments.
  • Proficiency with SQL and experience working with both structured and unstructured data sources.
  • Strong problem-solving skills with an emphasis on scalability and performance optimization.

Interested in this position?

Apply directly on the company website

Apply Now

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