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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Machine Learning Principal Engineer - **Company:** Honda Dev. and Mfg. of Am LLC - **Location:** Raymond, OH, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Microsoft Azure, C++ (Programming Language), Software Quality, Continuous Integration, Data Infrastructure, Extract Transform Load (ETL), Python (Programming Language), Machine Learning, Tensorflow, Management of Software Versions, Feature Engineering, Data Ingestion, Pytorch, Convolutional Neural Networks, Scikit Learn, Information Technology, Machine Learning Operations, Docker - **Published:** September 10, 2026 - **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=2962645428-2 ## About the Role * Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field, or equivalent experience. * 8+ years of experience developing and deploying ML/AI systems; 3+ years in production environments. Other Job-Specific Skills * Hands-on experience with graph neural networks (GCNNs, GNNs, GATs, MPNNs) * Advanced proficiency in Python; C++ or Java is a strong plus for automotive contexts * Deep expertise in ML frameworks (PyTorch, TensorFlow, scikit-learn) * Strong foundation in statistics, optimization, and numerical methods * Hands-on experience deploying AI solutions on AWS/Azure (e.g., Amazon Bedrock) * Experience with LangGraph / LangChain & Strands SDK. * Experience with containers, pipelines, and MLOps tooling (Docker, MLflow, CI/CD) * Knowledge of model governance, compliance, and responsible AI frameworks * CAE/physics-informed ML, surrogate modelling, or simulation experience (preferred). * Prior knowledge of automotive or related design engineering work is a plus. ## Description Lead the design, development, and deployment of advanced AI and machine learning solutions supporting Honda's automotive R&D initiatives, with a focus on production-grade AI for vehicle development, simulation, manufacturing quality, and digital twins-owning solutions end-to-end and mentoring engineers while partnering with CAE, CAD, manufacturing, and data platform teams., * Lead development and validation of AI/ML solutions with measurable impact for automotive engineering - CAE, and manufacturing use cases. * Design and deploy AI surrogate models using Graph Convolutional Neural Networks (GCNNs) to augment/replace physics-based CAE. * Architect and deploy scalable cloud-based AI systems on AWS/Azure aligned with enterprise governance. * Own the full AI lifecycle: data ingestion, feature engineering, training, evaluation, deployment, and monitoring. * Implement MLOps and GenAIOps best practices (versioning, drift detection, CI/CD, traceability). * Develop and deploy agentic AI solutions for CAE in the cloud and deploy AI agents to execute/augment/monitor workflows. * Support ETL activities related to ADC data (CAE) structure. * Establish design standards, code quality, and documentation to support reuse and auditability. * Mentor and technically guide mid-level and junior engineers. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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