AI Machine Learning Engineer

Role Overview: Lead the design, development, and deployment of advanced AI and machine learning solutions for automotive R&D, focusing on production-grade AI for vehicle development, simulation, manufacturing quality, and digital twins. Mentor engineers and collaborate with CAE, CAD, manufacturing, and data platform teams to deliver end-to-end AI solutions.

Key Responsibilities

• Develop and validate impactful AI/ML solutions for automotive engineering and manufacturing use cases.
• Design and implement AI surrogate models using Graph Convolutional Neural Networks (GCNNs) to augment physics-based CAE.
• Architect and deploy scalable cloud-based AI systems on AWS/Azure, ensuring compliance with enterprise governance.
• Manage the full AI lifecycle: data ingestion, feature engineering, training, deployment, and monitoring.
• Implement MLOps and GenAIOps best practices, including versioning, drift detection, CI/CD, and traceability.
• Create agentic AI solutions for CAE workflows and support ETL activities related to ADC data.
• Establish design standards, ensure code quality, and document processes for reuse and auditability.
• Mentor and guide mid-level and junior engineers.

Qualifications & Skills

• Bachelor’s or Master’s 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.
• Hands-on expertise with graph neural networks (GCNNs, GNNs), advanced Python skills, and familiarity with C++/Java.
• Proficiency with ML frameworks like PyTorch, TensorFlow, scikit-learn.
• Experience deploying AI on cloud platforms (AWS/Azure), with knowledge of containers and MLOps tools.
• Strong foundation in statistics, optimization, and numerical methods; experience with CAE or physics-informed ML is a plus.
• Prior automotive or engineering experience is advantageous.

Work Environment: Primarily office-based with potential hybrid options; occasional travel and overtime may be required to support project milestones.