machine learning engineer for routing cost recommendations

Mapbox provides a real-time location platform and tools for location-aware businesses to build navigation experiences for people, packages, and vehicles. Its Navigation team develops and operates web services for consumer, automotive, and logistics navigation initiatives, working across distributed systems, geospatial localization, traffic telemetry, and mapping.

• Lead engineering teams in delivering end-to-end feature implementation within the navigation organization
• Design and build ML and data pipelines, and optimize existing pipelines
• Build tools for automated quality assurance and data exploration
• Apply geospatial algorithms to optimize pipelines and create automated tuning and outlier detection algorithms
• Partner with data scientists to improve models that identify movement and traffic patterns
• Mentor colleagues and participate in code and design reviews
• Participate in an on-call rotation to maintain 24/7 system availability; primary responders may need to respond immediately outside normal working hours, including weekends

• 8–10+ Years of backend and ML experience
• Extensive hands-on engineering experience and a strong track record
• Extensive experience with Python, distributed processing pipelines (Hadoop, Spark, Airflow, Dask), and very large datasets, including statistical analysis, data quality control, and storage optimization
• Extensive experience with cloud and infrastructure services, including deploying and managing infrastructure in cloud environments
• Drive quality and continuous improvement, with a strong focus on clean code, robust architecture, and raising engineering practices and design standards
• Own technical vision, lead strategy, and guide the team in developing the routing cost engine
• Focus on customers and their problems, and innovate on their behalf
• Be open to learning from mistakes and developing professionally
• Experience mentoring and leading engineering teams, including supporting skill development and career growth
• Strong written and verbal communication skills; explain complex ideas concisely, lead and resolve organization-wide technical discussions, and collaborate with cross-functional security, devops, data, compliance, and product teams
• Use data-informed decision-making and measure important factors, including when data is incomplete
• Discuss how AI is used in the engineering workflow during the interview process

• Annual compensation ranges from $102.000 - $153.000 USD; job level and actual compensation depend on qualifications, skills, relevant experience, potential impact, and role scope
• On-call rotation may require immediate responses outside normal working hours, including weekends
• Supportive health care, parental leave, and flexibility for personal needs