Machine Learning Engineer

Job description

Roadie, a UPS Company, is a crowdsourced delivery platform. Founded in 2014, Roadie works with consumers, small businesses and enterprises across virtually every industry to enable scheduled, same day and urgent delivery in passenger vehicles across the U.S. With more than 200,000 drivers nationwide, Roadie reaches more than 20,000 zip codes – the largest local same-day delivery network in the nation.

As a Machine Learning Engineer at Roadie, you will build algorithms and models that run our core systems, from matching deliveries and drivers in a two-sided market to routing optimizations and dynamic pricing schemes. Collaborating with software engineers and data scientists, you will create technology solving real-world problems in the crowdsourced delivery space. This position will initially be focused on machine learning capabilities with marketplace pricing.

What You’ll Be Doing

  • Design, build and maintain new machine learning pipelines at the intersection of crowdsourced systems and logistics
  • Creatively apply the state of the art in machine learning to optimize Roadie’s automated decision-making
  • Build new pricing solutions for our expanding delivery marketplace
  • Work with engineers, product managers and designers on a cross functional team to implement the pipelines in a production environment
  • Advocate for data driven decision making throughout the company

What You Bring

  • MS or PhD in Machine Learning, Artificial Intelligence, Statistics, Computer Science, Operations Research or a related field
  • 2+ years of experience with applied machine learning
  • Extensive hands-on experience with Python and SQL
  • Expertise in optimization, machine learning algorithms (unsupervised and supervised ) and statistical methods
  • Experience in evaluating model performance
  • Experience using machine learning in the context of pricing
  • Familiarity with libraries such as Pandas, Numpy, Scikit-Learn, SciPy, PyTorch, Tensorflow, Keras and related
  • Understanding of modern deep learning techniques such as CNN, RNN
  • Ability to effectively articulate technical challenges and solutions to multiple audiences


  • Experience with graph algorithms
  • Experience with containers, Docker, or Kubernetes
  • Experience with cloud environments such as AWS, GCP, or Azure
  • Experience building machine learning pipelines and full loop machine learning systems
  • Experience with dynamic programming, approximate dynamic programming, and/or optimal control theory

Why Roadie?

  • Competitive compensation packages
  • 100% covered health insurance premiums for yourself
  • 401k with company match
  • Tuition and student loan repayment assistance (that’s right - Roadie will contribute directly to your existing student loans!)
  • Flexible work schedule with unlimited PTO
  • Monthly 3-day weekends
  • Monthly WFH stipend
  • Paid sabbatical leave - tenured team members are given time to rest, relax, and explore
  • The technology you need to get the job done

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