This Time, It's Personal with Adobe and Movable InkGet blockbuster results and epic journeys when AI-powered personalization meets Adobe Experience Cloud.Movable Ink scales content personalization for marketers through data-activated content generation and AI decisioning.
The world's most innovative brands rely on Movable Ink to maximize revenue, simplify workflow and boost marketing agility.
Headquartered in New York City with close to 600 employees, Movable Ink serves its global client base with operations throughout North America, Central America, Europe, Australia, and Japan.As a machine learning engineer, you will be part of our Applied AI and Machine Learning team.
You will work alongside other scientists and engineers in a collaborative environment, contributing features and machine learning models to our core recommender systems and our DaVinci Personalization product.
This is an opportunity to work end-to-end on a large-scale machine-learning system that touches millions of customers, and a chance to continuously learn and help improve our solution as the field evolves.Responsibilities:Generate insights into customer behavior and derive modeling ideas for improving our content recommender systemWork with data engineers to define what additional customer data we might want to collect and help make it available in a format suitable for modeling purposesCreate meaningful machine-learning features that improve our content recommender's performance measured through offline metrics and online a/b testsBuild machine learning models and deploy them as part of our recommender systemQualifications:Master's degree or equivalent experience (2+ years) in a relevant field or industrySolid understanding of machine learning fundamentalsHigh comfort level in Python or other programming languageFamiliarity with an ML stack such as typical scientific Python libraries (pandas, numpy, sklearn, xgboost) or deep learning frameworks (we use Pytorch)Familiarity with data analysis through SQL or a big-data processing framework such as SparkAbility to collaborate with technical partners – you'll be working closely with other teams to determine requirements for your work and to make design decisions that affect our stackThe idea of writing and deploying production code, and getting real-world feedback on your models excites youA desire to always be learning and contributing to a collaborative environment#J-18808-Ljbffr