Share
- Build models to generate recommendations and run them as large scale A/B tests directly on the retail website.Key job responsibilities
The role is focused on recommender systems bridging Generative AI, Natural Language Processing (NLP), Reinforcement Learning (RL), graph networks, and deep learning to help find the next great read for Books customers. You will build recommendation model pipelines, identify technical opportunities within complex deep learning-based recommendation models, and work with engineering and product leaders to power customer-facing recommendations.As part of the team, you will be exposed to all of these areas and have opportunities to hone and apply your skills across our problem space.A day in the life
From day-to-day, you will research and develop models that power customer facing recommendations, design and implement A/B test experiments, as well as collaborate with engineers, product, and other scientists to get machine learning solutions into production.
- 4+ years of applied research experience
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Experience in applied research
These jobs might be a good fit