Physical AI Engineer – Model

42dot

Physical AI Engineer developing next-generation end-to-end AI models for autonomous driving systems. Integrating advanced learning techniques to enhance real-world robotic performance.

Posted 7/20/2026full-timePangyo • 🇰🇷 South KoreaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Data Preprocessing, Model Training, and Performance Validation for AI models, with a strong focus on Model-Based Reinforcement Learning and Imitation Learning. Proficient in integrating and validating Motion Planning, Filtering, and Navigation algorithms in both simulation and real-world environments.

Highest-signal resume keywords

Python ProgrammingDeep Learning FrameworksModel-Based Reinforcement LearningMotion Planning AlgorithmsAI Model Validation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data PreprocessingModel TrainingPerformance ValidationImitation LearningMotion PlanningKalman FilterParticle FilterCUDA OptimizationMachine LearningDeep Learning

Tools & Technologies

PyTorchJAX

Industry Keywords

AI SystemsSimulationReal Vehicle EnvironmentsNavigation Algorithms

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Data preprocessing, model training, and performance validation for end-to-end trajectory generation and decision-making models
Model-Based Reinforcement Learning (MBRL) and Imitation Learning (IL) algorithm development and optimization
Integration and validation of motion planning, filtering (e.g., Kalman Filter, Particle Filter), and navigation algorithms
Support on-device optimization of deep learning models and planning pipelines using CUDA for real-time performance
Validate AI models and algorithms in simulation and real vehicle environments
Collaborate with perception, planning, and control teams to develop next-generation physical AI systems

Requirements

What you’ll need

컴퓨터공학, 전자공학, 로봇공학, 항공우주공학 또는 관련 분야 석사 학위 이상 또는 이에 준하는 실무 경험
Python 및 최신 딥러닝 프레임워크(PyTorch, JAX)를 활용한 AI 모델 개발 및 학습 경험
Motion Planning, Filtering, Navigation 알고리즘에 대한 이론적 이해 및 구현 경험
Simulation 또는 실제 Hardware 환경에서 AI 모델 및 알고리즘 검증 경험
머신러닝, 딥러닝 및 강화학습에 대한 이해

Benefits

Comp & perks

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