Machine Learning Engineer
- Employer
- Amazon Fashion
- Location
- Seattle, Washington State
- Closing date
- 8 Aug 2020
View more
- Function
- Technology
- Level
- Manager
- Contract Type
- Permanent
- Hours
- Full Time
Try Before You Buy (TBYB) team at Amazon Fashion is looking for a Machine Learning Engineer to join us to build our next-generation personalized recommendation systems for Personal Shopper, a new styling service for Prime members. In this role, you will be responsible for building scalable machine learning models and algorithms and automate their application and expansion to power customer-facing features.
Prior knowledge in one or more domains such as AI, ML, NLP, and CV is important. However, strong motivation to learn them is critical for successful candidates.
The primary responsibilities of this role include:
- Design and build automated pipelines to train and deploy ML models
- Scale ML algorithms
- Develop prototypes to test new concepts/proposals for models and algorithms
- Automate expansion of models to new geographies and segments
- Promote engineering excellence within science team
Basic qualifications
- 2+ years' non-internship professional experience in software development and system design
- Programming experience with at least one modern programming language such as Python, Java, Scala, or C++
- Bachelor’s Degree in Computer Science, Electrical Engineering, Statistics, Mathematics, or related disciplines
Preferred qualifications
- Experience in building scalable machine learning infrastructure in one of the application domains such as recommendation, computer vision, natural language processing, etc.
- Knowledge in machine learning, artificial intelligence, data mining, statistics, etc.
- Experience with Big Data technologies such as Hadoop, Spark, Pig, Hive, Presto, HBase, etc.
- Strong proficiency with Python, Java, Scala, or C++
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
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