Machine Learning Engineer, MLOps/MLaaS, Engine AI Center of Excellence

Machine Learning Engineer, MLOps/MLaaS, Engine AI Center of Excellence

DESCRIPTION

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 with 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 methods. In 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.

Key job responsibilities
– You design model experimentation in synergy with our scientists.
– You own the development and operationalization of solutions deployed in production.
– You work across multiple teams to integrate our solutions with products owned by our partners.
– You help the team grow and cultivate best practices in software development, MLOps, and experimentation.

A day in the life
Almost every day offers new challenges and opportunities for growth. Where one day will offer implementation of experimentation tooling, the next day may be focused on our operational excellence in maintaining our code base. Later in the week, you may sort technical challenges with our partners to help them enrich their products with our models. On some days or weeks, you may watch over our products and stand ready to intervene and provide support to partners consuming our models.

About the team
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 other’s skills. Together, we are a powerful team of specialists that bring the potential of practical machine learning to the max with impact on millions of Amazon customers.

BASIC QUALIFICATIONS
– Bachelor’s degree in computer science or equivalent
– Experience (non-internship) in professional software development
– Experience designing or architecting (design patterns, reliability, and scaling) of new and existing systems
– 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.

PREFERRED QUALIFICATIONS
– Master’s 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 machine learning, data mining, information retrieval, statistics, or natural language processing

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify, and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice to know more about how we collect, use, and transfer the personal data of our candidates.

#J-18808-Ljbffr