Job description

Role Overview:

Lead the design, development, and deployment of advanced AI and machine learning solutions supporting 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.

Key Responsibilities

Develop and validate impactful AI/ML solutions for automotive engineering and manufacturing use cases.
Design and implement AI surrogate models, such as Graph Convolutional Neural Networks (GCNNs), to augment or replace physics-based CAE.
Architect and deploy scalable cloud-based AI systems on AWS/Azure, ensuring adherence to enterprise governance.
Manage the full AI lifecycle: data ingestion, feature engineering, training, evaluation, deployment, and monitoring.
Implement MLOps and GenAIOps best practices, including versioning, drift detection, CI/CD, and traceability.
Develop agentic AI solutions and deploy AI agents to automate and monitor workflows.
Support data activities related to CAE structures and establish design standards, code quality, and documentation.
Mentor and guide junior engineers in technical tasks.

Qualifications & Skills

Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field, or equivalent experience.
8+ years in developing and deploying ML/AI systems, with 3+ years in production environments.
Hands-on experience with graph neural networks (GCNNs, GNNs, GATs, MPNNs), Python, and ML frameworks like PyTorch and TensorFlow.
Proficiency in deploying AI solutions on cloud platforms (AWS/Azure), with knowledge of containers, pipelines, and MLOps tools.
Strong foundation in statistics, optimization, and numerical methods; familiarity with responsible AI frameworks.
Experience in CAE, physics-informed ML, surrogate modeling, or simulation is preferred; automotive or engineering background is a plus.

Additional Details:

Work primarily at an office desk with potential hybrid options; occasional travel and overtime may be required. The role involves supporting cross-functional teams in a collaborative environment.