Machine Learning Engineering

Our team builds data-driven automation capabilities to support critical service operations in Retail and IT with global impact. Automation improves the operations and availability of consumer services with a positive impact on millions of users every year. We leverage off the sciences of data and information processing to build tooling and machine learning capabilities. Our work contributes to increase service operation resilience and enables us to act ahead of service disruptions while simplifying system and information complexity.

As a Machine Learning Engineer of the AICE team you have an important role in implementing and operating end-to-end machine learning and data processing pipelines that integrate with our partners production systems. You work in synergy with our applied scientists data scientists machine learning engineers and partners to design machine learning models and evaluation experiments at scale.

You are well familiar to all aspects of practical machine learning encompassing sound use of data preprocessing techniques analysis modelling (e.g. neural networks regression estimators probabilistic models etc.) hyper-parameter tuning approaches and validation addition you demonstrate excellent software development engineering skills that you use daily for designing computationally effective solutions and for machine learning operations (MLOps) in large scale production environments.

You help the team grow and cultivate best practices in software development MLOps and experimentation.

On some days or weeks you may watch over our products and stand ready to intervene and provide support to partners consuming our models.

We work back to back to address the technical challenges of automation across a variety of products software and systems. Our scientists and machine learning engineers work in synergy to solve hard problems and enrich each others skills. Together we are a diverse team of specialists that bring the potential of practical machine learning to the max with impact on millions of Amazon customers.

• Bachelors degree or equivalent
• Experience (non-internship) in professional software development
• Experience programming with at least one software programming language
• Experience in Machine Learning Operations (MLOps) in deploying operationalizing and maintaining scalable AI/ML-solutions in production.
• Masters degree in computer science or equivalent
• Experience with full software development life cycle including coding standards code reviews source control management build processes testing and operations
• Experience in several of the following areas: machine learning statistics deep learning natural language processing or information retrieval

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