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ML Data Engineer

Before you read on, take a look around you. Chances are, pretty much everything you see has been shipped, often multiple times, in order to get there. E-commerce is exploding, and with it, parcel shipping is becoming a meaningful factor in a business' ability to succeed. Creating a compelling shipping experience for customers is hard but necessary.


At Shippo, our goal is to level the playing field by providing businesses access to shipping tools and terms that would not be available to them otherwise.


Shippo lowers the barriers to shipping for businesses around the world. As free and fast shipping becomes the norm, better access to shipping is a competitive advantage for businesses. Through Shippo, e-commerce businesses, marketplaces, and platforms are able to connect to multiple shipping carriers around the world from one API and dashboard. Businesses can get shipping rates, print labels, automate international documents, track shipments, and facilitate returns.


Internally, we think of Shippo as the building blocks of shipping. Shippos are a diverse set of individuals. We look for cultural and skill fit in every new person. Join us to build the foundations of something great, roll up your sleeves, and get important work done everyday. Founded in 2013, we are a proud team based out of San Francisco. Shippo’s investors include D1 Capital Partners, Bessemer Venture Partners, Union Square Ventures, Uncork Capital, VersionOne Ventures, FundersClub, and others.


As an ML Data Engineer, you will work closely with Data Scientists and other Engineers to lead the design and implementation of ML algorithms. You will work closely with the data scientists to understand data and infrastructure needs for deployment and design feedback loops for machine learning algorithms. You will create dashboards to monitor the performance of the model and monitor decay. You will also be responsible for working with downstream engineering teams and own the API data contract. You will work with the cloud engineering teams to ensure load balancing in order to meet production SLAs. 


Responsibilities

  • Deploy machine learning algorithms to production
  • Responsible for system architecture design 
  • Monitor model performance in production
  • Innovating by recognizing opportunities for automation and tools improvements 
  • Responsible for developing and implementing process improvements to bring efficiency and stability 
  • Provide technical leadership for a team of data scientists 
  • Responsible for release engineering
  • Provide, promote, and accept feedback and guidance (from all levels) to promote a culture of continuous improvement, collaboration, and shared knowledge 


Requirements

  • Mastery of Python
  •  3+ years of experience in software engineering/data science 
  • Experience building data science or data analysis tools
  • Some experience with Docker, Kubernetes, or cloud platform deployment 
  • Experience with Relational databases and NoSQL databases 
  • Demonstrated understanding of the full software development lifecycle 
  • Excellent problem solving, critical thinking, and communication skills 
  • Solid grasp of computer science fundamentals including data structures and algorithms 
  • Ability to work on multiple ML projects 
  • Experience with AWS Sagemaker is a plus


Benefits

  • Benefits: medical, dental, vision, (90% covered by the company, incl. dependents), and pets coverage
  • Flexible PTO + work hours
  • Dog are welcomed in the office
  • 3 VTO days for ShippoCares volunteering events
  • $2,500 yearly learning stipend for your personal growth
  • Free lunch / drinks / snacks
  • Fun team events outside of work hours - happy hours, “escape room” adventures, hikes, and more!

Company

Shippo

Location

San Francisco, Austin, or RemoteFlexible

Job type

Full-Time

Category

Machine Learning

Tags

AWSDockerKubernetesNoSQL
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