- PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
- Experience programming in Java, C++, Python or related language
- Research and/or work experience in Deep Learning, Recommendation System, Natural Language Processing (NLP), or Computer Vision.
Are you passionate about solving unique customer-facing problem in the Amazon scale? Are you excited by developing and productizing machine learning, deep learning algorithms and leverage tons of Amazon data to learn and infer customer shopping patterns? Do you enjoy working with a diversity of engineers, machine learning scientists, product managers and user-experience designers? If so, you have found the right match!
Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique problem domains such as product recommendations, product discovery and evaluation. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for Fashion customers by providing large selections, inspiring and accurate recommendations and customer experience.
The mission of Fit science team as part of Fashion Tech is to innovate and develop scalable ML solutions to provide personalized fit and size recommendation when Amazon Fashion customers evaluate apparels or shoes online. The team is hiring Applied Scientist who has a solid background in applied Machine Learning and a proven record of solving customer-facing problems via scalable ML solutions, and is motivated to grow professionally as an ML scientist.
Key job responsibilities
- Tackle ambiguous problems in Machine Learning and drive full life-cycle Machine Learning projects.
- Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production.
- Run A/B experiments, gather data, and perform statistical tests.
- Establish scalable, efficient, automated processes for large-scale data mining, machine-learning model development, model validation and serving.
- Work closely with software engineers and product managers to assist in productizing your ML models.
- Published research work in academic conferences or industry circles.
- Experience with deep learning tools like TensorFlow or PyTorch.
- Experience in building large-scale machine-learning models and infra for recommendation system.
- Effective and crisp verbal and written communication skills with non-technical and technical audiences.
- Experience working with very large real-world data sets and building scalable models from big data.
- Demonstrated successful industrial experience, drives results.
- Exhibits excellent business judgment and understanding of science, engineering, and business trade-offs.
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.