Machine Learning Engineer

We're looking for ML Engineers!
Responsibilities:
Design ML Solutions: Design production-ready ML software, distributed systems, and ML components that are efficient, scalable, and maintainable.
Develop ML Algorithms: Apply various ML algorithms, including regression, classification, clustering, and recommender systems, using popular libraries such as scikit-learn, TensorFlow, or PyTorch.
Deploy ML Systems: Deploy designed ML solutions, ensuring they meet production standards and are integrated with existing systems.
Optimize ML Performance: Ensure ML solutions are efficient, scalable, and maintainable, and optimize their performance as needed.
Maintain ML Components: Maintain and update existing ML components to ensure they remain efficient and effective.
Qualifications:
Machine Learning Techniques: Experience with machine learning techniques and their applications, including regression, classification, clustering, and recommender systems.
ML Algorithm Development: Experience in applying various ML algorithms using popular libraries such as scikit-learn, TensorFlow, or PyTorch to design and develop production-ready ML software and components.
Distributed Systems Design: Experience designing and deploying distributed systems and ML components that are efficient, scalable, and maintainable.
Production-Ready Software Development: Experience developing and deploying production-ready ML software that meets production standards and integrates with existing systems.
Performance Optimization: Experience optimizing the performance of ML solutions to ensure they remain efficient and effective.
(Note: Relevant applicants will receive an email requesting additional information as part of the next stage. The application process will be completed directly on the team's designated platform, and all subsequent communication and decisions regarding the opportunity are managed by the respective hiring team.)

Work arrangement
Hybrid