Amazon Web Services, Inc. is looking to solve business and engineering problems using machine learning (ML) and natural language (NL) applications
Requirements
- Programming in Java, C++, Python, or equivalent programming language
- Conducting the analysis and development of various supervised and unsupervised machine learning models for moderately complex projects in business, science, or engineering
- Statistical modeling techniques (e.g. Bayesian models and deep neural networks)
- Optimization methods
- Other ML techniques
- Machine learning (ML) and natural language (NL) applications
- Deep neural networks
Responsibilities
- Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications
- Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering
- Routinely build and deploy ML models on available data, and run and analyze experiments in a production environment
- Identify new opportunities for research in order to meet business goals
- Research and implement novel ML and statistical approaches to add value to the business
- Mentor junior engineers and scientists
- Conducting the analysis and development of various supervised and unsupervised machine learning models for moderately complex projects in business, science, or engineering
Other
- Master’s degree or foreign equivalent in Computer Science, Machine Learning, Engineering, or a related field and two years of research or work experience in the job offered, or as a Research Scientist, Research Assistant, Software Engineer, or a related occupation
- Bachelor’s degree or foreign equivalent in Computer Science, Machine Learning, Engineering, or a related field and five years of research or work experience in the job offered or a related occupation
- One year of research or work experience
- Telecommuting may be permitted
- 40 hours / week, 8:00am-5:00pm
