As a Senior Machine Learning Engineer in our Driver Telemetry Team, you will play a pivotal role in developing and deploying machine learning models that improve our delivery operations. You will work closely with data scientists, engineers, and product managers to create innovative solutions that enhance driver behavior analysis, route optimization, and beyond, utilizing geo-spatial insights to drive these advancements.


A critical aspect of your role involves partnering with software engineers to ensure the seamless operationalization of your models into our production systems. The work you do will not only bring your machine learning expertise to life in real-world applications but will also have a direct and measurable impact on the daily experiences of our drivers and customers, driving significant advancements in our service quality and operational efficiency.

Responsibilities Include:

  • Developing data pipelines that effectively handle and process geo-spatial and event data, ensuring high-quality inputs for analyses and modeling.
  • Building reliable, efficient, and scalable models for our ML capabilities.
  • Evaluating the impact and effectiveness of models in production systems.
  • Developing and implementing advanced machine learning algorithms to analyze driver behavior, predict potential risks, and enhance operational efficiency.
  • Continuously exploring advancements in geo-spatial (and other) machine learning technologies and their potential applications in enhancing telemetry systems.
  • Helping shape roadmaps by integrating business context and Data Science.



What You Bring: 

Core Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Statistics, Applied Mathematics, or a related field.
  • Minimum of 5 years of experience in machine learning, data science, or a related field.
  • Demonstrated proficiency in commonly used machine learning frameworks and libraries.
  • Solid experience in MLOps practices, including automation, monitoring, and maintaining machine learning models in production environments.
  • Proven track record in developing advanced machine learning models, preferably with a specialization in handling and analyzing geo-spatial or “real-time” event data.
  • Proficiency in using cloud computing platforms such as AWS, GCP, Azure, or similar for deploying and scaling machine learning models.
  • Experience working with non-technical stakeholders to solve acute business problems.


Preferred Qualifications

  • PhD in relevant field
  • Experience in the logistics, delivery, or transportation industry, with a focus on geo-spatial analytics.
  • Demonstrated experience in leading innovative projects in route optimization, driver behavior modeling, or similar fields.
  • Strong portfolio showcasing successful machine learning projects.
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