Principal AI Engineer - Off-Board Autonomy Lead

Pittsburgh Robotics Network; Pittsburgh (Allegheny County); Hybrid; USD 200,000 - 275,000; Full time

Benefits offered by this job

Hybrid schedule

Multiple office locations

Job summary

Motional is seeking a Principal Engineer to oversee the design, development, and deployment of an Embodied AI and LLM-based off-board evaluation framework for scenario understanding and root-cause analysis. You will shape a scalable data pipeline and integrate with the autonomy stack to drive safety metrics across fleet data.

Hybrid work is encouraged with in-office time in Boston, Pittsburgh, or Las Vegas, or fully remote options in the U.S.

Qualifications

• 10+ years of software/AI/AV systems experience.
• Bachelor's degree in Computer Science, Engineering, Robotics, or related field.
• Proven experience with LLMs and Vision-Language Models for reasoning and scene description.
• Experience with parameter-efficient fine-tuning and deploying open-weights models.
• Familiarity with vector databases and data pipelines.
• Experience with AV performance metrics development and validation.
• Strong Python proficiency and software engineering fundamentals.

Responsibilities

• Oversee design, development, and deployment of off-board evaluation framework.
• Lead integration of Embodied AI with AV data pipelines for safety scoring.
• Drive root-cause analysis and actionable insights for Autonomy team.
• Collaborate across autonomy, infrastructure, and operations groups.
• Provide technical leadership and mentorship to engineers.

Skills

LLMs & VLMs for reasoning

Python

Autonomous vehicle systems

AI/ML

Data pipelines

Adversarial scenarios

Debugging & performance

Education

Bachelor's degree in CS/Engineering/Robotics

Tools

LanceDB

AWS/GCP

Ray

C++

Job description

Motional is seeking a Principal Engineer to oversee the design, development, and deployment of an Embodied AI and LLM-based off-board evaluation framework for scenario understanding and root-cause analysis. You will shape a scalable data pipeline and integrate with the autonomy stack to drive safety metrics across fleet data.

Hybrid work is encouraged with in-office time in Boston, Pittsburgh, or Las Vegas, or fully remote options in the U.S.