Software Development Engineer (Machine Learning)

About the role

Amazon Europe is looking for a Specialised Software Development Engineer focused on machine learning. You will help build and deploy ML solutions that power Amazon Q, optimize European operations, improve retail search matching for EU customers and enhance Amazon Music recommendations. The role works with ML engineers and scientists on natural language processing, computer vision and deep learning. It is not remote and may be available across several EMEA locations; applicants choose which locations they are open to.

Key responsibilities

• Develop and optimize ML models for production deployment at massive scale
• Build and maintain ML pipelines and infrastructure for model training and inference
• Design and implement efficient data processing and feature engineering solutions
• Create and enhance ML evaluation frameworks and monitoring systems
• Collaborate on improving model performance, latency and resource utilization
• Work with cross-functional teams to integrate ML solutions into product features
• Contribute to the development of ML platforms and tools used across Amazon

Required profile

• Graduated within the last 24 months or expected to graduate within the next 6 months with a Bachelor's or Master's degree in Computer Science, Computer Engineering or a related field
• Fluency in spoken and written English
• Strong knowledge of computer science fundamentals, including data structures, algorithms and object-oriented design
• Understanding of fundamental ML concepts and common frameworks (PyTorch, TensorFlow)

Required skills

• Proficiency in at least one programming language such as C, C++, Java, Python or Rust
• Knowledge of data structures and software engineering principles
• Preferred: previous ML/AI internship or project experience
• Preferred: experience with NLP, computer vision or recommendation systems
• Preferred: knowledge of ML deployment and MLOps, distributed systems and cloud platforms
• Preferred: familiarity with deep learning model optimization, large-scale data processing, ML evaluation metrics and A/B testing