We are The Selling App. The fast and easy way to sell or buy almost anything, from fashion to toys, sporting goods to electronics, jewelry to shoes. Launched in 2013, Mercari quickly became the #1 shopping app in Japan. Now we’re on a global mission to build a future where people everywhere feel empowered to sell the things they don’t use, a future where all useful things are used. And with a fast-growing user base in the U.S. of over 35 million downloads, we are on our way to doing just that.
The ideal candidate is eager to take on increasing responsibilities and preferably has the experience to develop end-to-end machine learning system in production.
Recent Engineering Achievements:
- At Go Bold Days (internal hackathon), we created instant listings where you can list an item with full details by just taking one picture.
- We built a data pipeline to analyze the status, weight, and cost of every item shipped on Mercari, and a machine learning model to suggest the best shipping options for sellers. This reduced shipping mistakes by over half.
- We also built a price scanner where you can get an estimate of the item price by pointing your phone's camera to it.
What You’ll Be Doing:
- Design and build machine learning systems with a massive amount of data.
- 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. Experience in Java, Python, Scala and other equivalent languages is a plus.
- 5+ years experience with end-to-end machine learning projects
- MS/PhD in Computer Science or related technical field.
- Experience with TensorFlow or related deep learning libraries.
- Experience with Apache Spark, Apache Beam a plus.
- Experience with developing microservices with docker and kubernetes to serve machine learning models.
- Experience with Google Cloud Platform / Amazon Web Services.
Technologies We Use
- Distributed Processing: Apache Beam/Apache Spark
- Cloud: Google Cloud(BigQuery/ML Engine/Google Dataflow/Google Dataproc, etc.)\
- Database: Google Datastore/MySQL/Google Spanner
- API: gRPC/Tensorflow Serving/Flask(REST)
- Container: Docker/Kubernetes
- Machine Learning: Tensorflow/Keras/Scikit-Learn, etc.
Mercari nurtures an all for one environment where teamwork and innovative thinking is the priority.
- Medical, Dental and Vision insurance options
- Commuter Reimbursement
- Time when you need it - Unlimited vacation days
- Catered lunches everyday
- Team outings and events