Job PurposeLead 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.
Key Accountabilities - 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.
Qualifications, Experience, and Skills - 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.
Job Dimensions Decisions Expected Working Conditions - Work is primarily conducted at an office desk; hybrid (office/home) work may be available.
- Occasional travel and overtime may be required based on project milestones.
- Work in a cross-functional environment supporting engineering, simulation, and manufacturing stakeholders.
Total Rewards: - Competitive Base Salary (pay will be based on several variables that include, but not limited to geographic location, work experience, etc.)
- Regional Bonus (when applicable)
- Manager Lease Car Program (No Cost - Car, Maintenance, and Insurance included)
- Industry-leading Benefit Plans (Medical, Dental, Vision, Rx)
- Paid time off, including vacation, holidays, shutdown
- Company Paid Short-Term and Long-Term Disability
- 401K Plan with company match + additional contribution
- Relocation assistance (if eligible)
Career Growth: - Advancement Opportunities
- Career Mobility
- Education Reimbursement for Continued learning
- Training and Development Programs
Additional Offerings: - Lifestyle Account
- Childcare Reimbursement Account
- Elder Care Support
- Tuition Assistance & Student Loan Repayment
- Wellbeing Program
- Community Service and Engagement Programs
- Product Programs
