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Principal Engineer – Tech Lead, Embodied AI, Off-Board Performance Evaluation
MotionalPrincipal Engineer overseeing Embodied AI development for autonomous vehicles at Motional. Focus on performance metrics and off-board evaluation systems in a leading tech environment.
Tech Stack
Tools & technologiesCloudPython
About the role
Key responsibilities & impact- Technically oversee the architecture to identify, describe, and enrich events in historical vehicle logs using Multimodal LLMs.
- Oversee the off-board ingestion and fusion of semantic scene descriptions, ego-centric kinematics, and internal autonomy telemetry to create a holistic diagnostic context for LLM inference.
- Develop structured prompting templates utilizing Contextual Prompting (CP), Chain-of-Thought (CoT), and In-Context Learning (ICL) to evaluate scenarios.
- Architect the integration of foundation models into the Metrics Engine (ME), designing efficient cascade filtering and log slice parallelization strategies to scale high-volume LLM inference across simulation and on-road drive logs while managing computational latency and costs.
- Define, design, and implement key metrics to evaluate autonomous vehicle performance, such as lane change capability, oscillations, and braking.
- Deploy and manage a Retrieval-Augmented Generation (RAG) vector database containing codified AV Driving Policies to ground off-board LLM evaluations in specific Operational Design Domains.
- Serve as a technical escalation point and collaborate with Autonomy (Planner, Prediction, Perception) and Systems teams to deliver high-signal, enriched events.
- Drive the transition toward Direct Vector-LLM Fusion utilizing emerging Physical AI ecosystems and open-weights Vision-Language-Action (VLA) models to process telemetry off-board without text-translation bottlenecks.
Requirements
What you’ll need- 10+ years of professional experience in software engineering, applied AI/ML, or autonomous vehicle systems development.
- Bachelor's degree in Computer Science, Engineering, Robotics, or a related field.
- Proven experience working with Large Language Models (LLMs) and Vision-Language Models (VLMs) for reasoning, parsing, and scene description.
- Experience with parameter-efficient fine-tuning and deploying open-weights models on internal infrastructure.
- Familiarity with local and cloud vector databases, such as LanceDB, for housing output vector embeddings.
- Experience with adversarial scenario generation and closed-loop simulation environments.
- Strong background leveraging software to develop frameworks, libraries, and tools for calculating and aggregating AV performance metrics.
- Strong analytical and problem-solving skills, particularly in the context of complex system performance evaluation.
- Expert-level proficiency in Python and strong understanding of software development principles.
Benefits
Comp & perks- medical
- dental
- vision
- 401k with a company match
- health saving accounts
- life insurance
- pet insurance
- more
ATS Keywords
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Hard Skills & Tools
Software EngineeringApplied AI/MLParameter-Efficient Fine-TuningAdversarial Scenario GenerationPerformance Metrics Calculation
Soft Skills
Analytical SkillsProblem-Solving Skills
Certifications
Bachelor's Degree in Computer ScienceBachelor's Degree in EngineeringBachelor's Degree in Robotics