
Machine Learning Engineer
Roadie, a UPS Company, is a logistics management and crowdsourced delivery platform. Founded in 2014, Roadie offers businesses fast, flexible and asset-light logistics solutions for last-mile delivery. Roadie enables local delivery to more than 95% of U.S. households by providing access to more than 200,000 independent drivers nationwide – allowing businesses to offer their customers delivery optionality for almost any industry, from airlines to artisans.
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 that solves real-world problems in the crowdsourced delivery space. This position will initially be focused on machine learning capabilities with marketplace pricing.
What You’ll Do
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 engineering, product and design 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 machine learning algorithms (unsupervised and supervised) and statistical methods
Experience in evaluating model performance
Experience using machine learning in the context of logistics
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
Bonus
Experience with graph algorithms
Experience with combinatorial or nonlinear optimization techniques
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
This role is not eligible for Visa sponsorship. Applicants must be authorized to work for any employer in the U.S.
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