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 50M+ downloads in the U.S. and 350k+ new listings every day, we're just getting started.

The ideal candidate is eager to take responsibilities on data products and machine learning platform spontaneously and has a passion to make our systems reliable and sustainable with modern technologies. The candidate will take responsibility for not only data engineering, but also our machine learning platform. We expect the candidate is able to design and implement data pipelines at scale and is deeply familiar with container technologies and related topics to offer intelligent systems as Microservices.

What You'll Be Doing:

  • Design, build and operate ETL pipelines at scale
  • Automate processes related to data products and machine learning products
  • Support stakeholders with designing data structure for data products
  • Building knowledge graph to support the Machine Learning Engineering team
  • Development and operation of API/tools related to data products and machine learning products

What You'll Need:

  • BS in Computer Science or related technical field
  • Industry experience building and productionizing data pipelines
  • Experience with Python
  • Strong experience with RDMS and SQL
  • Experience developing knowledge graphs for specific purposes, e-commerce experience a plus
  • Experience with Google Cloud Platform or AWS or related cloud services
  • Ability and desire to take full ownership of projects, driving them forward to completion

Nice-to-haves: 

  • Experience with Apache Spark, Apache Beam or related distributed processing frameworks
  • Experience with Apache Airflow or related workflow scheduling products
  • Experience with developing Microservices with docker and Kubernetes to serve machine learning models
  • Experience in the machine learning space

Technologies We Use:

  • ETL: Apache Airflow
  • Container: Docker/Kubernetes
  • API: gRPC/Tensorflow Serving/Flask(REST)
  • Database: Google Datastore/MySQL/Google Spanner
  • Distributed Processing: Apache Beam/Apache Spark
  • Machine Learning: Tensorflow/Keras/Scikit-Learn, etc.
  • Cloud: Google Cloud(BigQuery/ML Engine/Google Dataflow/Google Dataproc, etc.)

Perks:

  • Competitive ‌medical, dental, and vision insurance options
  • 401k match
  • Life & disability insurance
  • Employee Assistance Program
  • New parent paid leave
  • Rocket Lawyer legal services
  • Fond perks and rewards
  • Time when you need it - flexible vacation days

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