Lead ML Engineer - Routing & Geospatial AI

Mapbox; United States; Remote; USD 150,000 - 200,000; Full time

Job summary

Mapbox is seeking a Machine Learning Engineer III to lead the routing cost team’s ML initiatives and scalable backend systems in the United States. You will design, build, and optimize high-traffic ML pipelines and collaborate with data scientists on movement and traffic patterns.

You’ll mentor engineers, review designs, and participate in on-call rotations to ensure 24/7 availability of critical services. This role requires deep backend and ML expertise and a passion for geospatial data.

Qualifications

• 8-10+ years of backend and ML experience: Extensive hands-on experience showcasing expertise and a strong

Responsibilities

• Lead the engineering team(s) to execute end-to-end feature implementation within the larger navigation organization (~80 engineers).
• Design and build new ML and data pipelines, as well as optimizing existing ML and data pipelines.
• Build tools for automated quality assurance and data exploration.
• Leverage geospatial algorithms to optimize pipelines, as well as creating automated tuning and outlier detection algorithms.
• Partner with data scientists to make improvements to our models for determining patterns in movement and/or traffic.
• Mentor colleagues and participate in code and design reviews.
• Participate in an on-call rotation to ensure our systems remain available to customers 24/7. Team members alternate as the on-call primary responder, which may require immediate response outside normal working hours, including weekends.

Skills

Backend development

Machine learning

Leadership

Geospatial data

Job description

Mapbox is seeking a Machine Learning Engineer III to lead the routing cost team’s ML initiatives and scalable backend systems in the United States. You will design, build, and optimize high-traffic ML pipelines and collaborate with data scientists on movement and traffic patterns.

You’ll mentor engineers, review designs, and participate in on-call rotations to ensure 24/7 availability of critical services. This role requires deep backend and ML expertise and a passion for geospatial data.