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 200000 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.