Staff ML Engineer — Map Reconstruction (Remote)

General Motors; Carson City (NV); Remote; USD 185,000 - 335,000; Full time

Benefits offered by this job

Company vehicle program

Relocation benefits

Health benefits

Job summary

General Motors seeks a Staff Machine Learning Engineer to lead automated map reconstruction within the Mapping Engineering team. You will architect end-to-end ML/CV pipelines, process multi-modal sensor data, and deliver scalable map primitives for national deployments.

You will mentor engineers, define technical strategy, and drive cross-functional initiatives across Mapping, Perception, Localization, and Simulation. Remote work within the US is possible.

Qualifications

• 5+ years building and deploying production ML/CV systems.
• Strong foundation in computer vision, ML, or robotics with hands-on modeling.
• Proficiency in Python for ML; C++ familiarity is a plus.
• Experience leading cross-functional, technical initiatives with autonomy.

Responsibilities

• Architect end-to-end ML/CV map reconstruction pipelines at national scale.
• Lead offline data mining, labeling strategies, model training and eval.
• Define architecture for robust, scalable mapping capabilities.
• Advise on 3D perception, BEV representations, and multi-view geometry.
• Collaborate with Perception, Localization, Simulation, Platform teams.
• Mentor senior engineers and drive technical excellence across teams.
• Resolve system-level issues in data pipelines and production workflows.
• Act as SME for ML-based mapping within the AV org.

Skills

ML/CV experience

Python

Data pipelines

Leadership

Systems thinking

Education

BS/MS/PhD in CS, EE, Robotics

Job description

General Motors seeks a Staff Machine Learning Engineer to lead automated map reconstruction within the Mapping Engineering team. You will architect end-to-end ML/CV pipelines, process multi-modal sensor data, and deliver scalable map primitives for national deployments.

You will mentor engineers, define technical strategy, and drive cross-functional initiatives across Mapping, Perception, Localization, and Simulation. Remote work within the US is possible.