Mercari is the selling app. We make it super easy to sell (or buy) almost anything. We all have things we don't use, never used or simply outgrew. But that stuff still has value. Mercari gives you the power to simply sell it, ship it, and earn some cash for it. Fashion to toys. Sporting goods to electronics. All the brands you know and love. Our mission is simple: to make selling easier than buying. And with 45m+ downloads in the U.S. and 150k new listings every day, we're just getting started.
As Machine Learning Engineer at Mercari, you have the experience to develop end-to-end machine learning system in production and eager to take on increasing responsibilities
What You'll Be Doing:
Design and build machine learning systems with a massive amount of data (Textual and Visual data of our listing inventory).
Use machine learning, deep learning, natural language processing to make models across recommendation, search, image recognition and so on.
What You'll Need:
Industry experience building and producing innovative end-to-end Machine Learning systems
Experience working on production machine learning systems at scale, data mining, ranking, recommendations, and/or natural language processing
Solid engineering and coding skills. Ability to write high-performance production quality code
General: Deep understanding of machine learning algorithms, deep neural network architectures, clustering. Classifications and sequence2sequence models
NLP: Experience in at least two of the following NLP systems: sentiment analysis, parsers, personal assistance systems (i.e, chatbots), ranking, recommendation
MS/PhD in Computer Science or a related technical field
1+ years experience with end-to-end machine learning projects
Experience with TensorFlow or related deep learning libraries
Deep understanding of probabilistic models, statistical modeling and stochastic systems
Strong programming skills in Python
Experience with developing microservices with Docker and Kubernetes to serve machine learning modelsExperience with Google Cloud Platform / Amazon Web Services
Experience with Flask, Apache Spark, Apache Beam a plus
Technologies We Use:
Machine Learning/Deep learning: Tensorflow/Keras/Scikit-Learn, etc.
Cloud: Google Cloud (BigQuery/ML Engine/Google Dataflow/Google Dataproc, etc.)
Database: Google Datastore/MySQL/Google Spanner
API: gRPC/Tensorflow Serving/Flask (REST)
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