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Machine Learning Scientist, ATS Machine Learning and Engineering
hace 2 meses
About the Role
We are seeking a highly skilled Machine Learning Scientist to join our team at Amazon Transportation Services (ATS). As a key member of our Science and Technology team, you will be responsible for developing and researching machine learning solutions and algorithms for core planning systems, as well as other applications within ATS.
Key Responsibilities
- Design and implement machine learning models for business applications, leveraging expertise in areas such as time series forecasting, optimization, and graph neural nets.
- Collaborate with cross-functional teams to integrate machine learning solutions into our transportation systems, ensuring seamless integration and optimal performance.
- Conduct research and development of new machine learning techniques and algorithms, staying up-to-date with the latest advancements in the field.
- Work closely with data engineers to design and implement scalable data pipelines, ensuring high-quality data for machine learning model training and deployment.
- Develop and maintain patents and publications at top-tier peer-reviewed conferences and journals, showcasing expertise and innovation in machine learning.
Requirements
- PhD or Master's degree in Computer Science, Electrical Engineering, Machine Learning, or a related field.
- Experience in building models for business applications, with a strong background in machine learning, time series forecasting, and/or optimization.
- Experience in programming languages such as Java, C++, Python, or related languages.
- Experience in areas such as algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, and high-performance computing.
Preferred Qualifications
- Experience using Unix/Linux operating systems.
- Experience in professional software development, with a strong understanding of software engineering principles.
About Amazon
Amazon is an equal opportunities employer, committed to diversity and inclusion in the workplace. We believe that employing a diverse workforce is central to our success, and we strive to create an environment where everyone can thrive.
