About the Role
Alexa Shopping is at the intersection of Machine Learning and the Amazon Retail experience, helping millions of customers worldwide with daily shopping needs. The Language Interpretation team within Alexa Shopping Natural Language Understanding (NLU) focuses on developing language interpretation solutions to create engaging shopping discourse, reduce friction, and enable CX teams to quickly release features across all locales by normalizing natural language.
As An ML Engineer, You Will Be Expected To
- Work with Applied Scientists, Data Scientists, Research Scientists, ML Engineers, and Software Engineers to design and deliver ML solutions in production at scale.
- Develop ML workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure the quality of architecture and design of our ML systems and data infrastructure.
- Deliver customer facing and internal ML solutions to enable the best experience for our customers.
Basic Qualifications
- Bachelor’s Degree in Computer Science or equivalent experience.
- 2+ years professional experience in software development.
- Computer Science fundamentals in object-oriented design.
- Computer Science fundamentals in data structures.
- Computer Science fundamentals in algorithm design, problem solving, and complexity analysis.
- Knowledge of, at least, one modern programming language such as Java, C++, C, Java, or Perl.
Preferred Qualifications
- 3+ years of experience building scalable ML infrastructure and big data systems.
- Experience successfully mentoring junior ML Engineers.
- High attention to detail and proven ability to manage multiple, competing priorities simultaneously.
- Proficiency with Apache Spark and Amazon AWS platform (SageMaker, Redshift, EMR, Glue, Step Functions, Lambda, Batch, etc.).
- Experience with ML libraries and deep learning frameworks (MXNet, TensorFlow, etc.).
- Experience with Speech and/or NLU (Natural Language Understanding), NLP (Natural Language Processing) systems.
- Experience with end-to-end software development and life cycle of ML solutions.
- Excellence in technical communication with scientists and engineers.