Machine Learning Engineer

Summary

Join Roadie, a UPS company and crowdsourced delivery platform, as a Machine Learning Engineer. You will design, build, and maintain machine learning pipelines for optimizing delivery matching, routing, and pricing. Collaborating with engineers and data scientists, you'll apply cutting-edge machine learning techniques to solve real-world logistics problems. This role focuses on marketplace pricing and requires expertise in machine learning algorithms, Python, and SQL. Roadie offers competitive compensation, comprehensive benefits including 100% covered health insurance and flexible work arrangements.

Requirements

• 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

Responsibilities

• 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

Preferred Qualifications

• 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

Benefits

• 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