AI Technical Lead - Cloud & Full-Stack Development

Stellantis NV•Auburn Hills, MI

49d

About The Position

We are seeking a highly skilled and hands-on AI Technical Lead to drive the development and deployment of intelligent systems across cloud and full-stack environments. This role combines leadership, architecture, and development responsibilities, requiring deep expertise in machine learning, cloud infrastructure, and full-stack engineering. You will lead cross-functional teams to deliver scalable AI solutions that integrate seamlessly into enterprise applications. Additionally, the AI solutions being developed are for vehicle engineering, testing, simulations, and homologation. Therefore, this role bridges the gap between IT and engineering, ensuring that digital tools, systems, and infrastructure align with the needs of vehicle development, testing, and production. Basic knowledge of vehicle design and testing is required for success.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, or related field.
7+ years of experience in software development, with 3+ years in AI/ML.
Strong programming skills in Python and JavaScript (React, Node.js).
Proven experience with cloud platforms (AWS, Azure, or GCP).
Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
Experience building and deploying full-stack applications.
Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines.
Excellent communication and leadership skills.

Nice To Haves

Experience with MLOps tools (Python, MLflow, Airflow, SageMaker, Vertex AI).
Knowledge of data engineering tools (Spark, Kafka, Databricks, Snowflake).
Contributions to open-source AI projects or publications.
Certifications in cloud or AI technologies.

Responsibilities

Design and maintain IT architecture supporting vehicle testing systems, including data acquisition, test automation, telemetry, and analytics platforms.
Collaborate with engineers, IT teams, and operations to align technology solutions with testing requirements and regulatory standards.
Lead the design, development, and deployment of AI/ML models and systems across cloud platforms (AWS, Azure, GCP).
Architect and implement full-stack solutions integrating AI models with front-end and back-end components.
Deploy the cloud environments and components needed for new AI projects.
Collaborate with data scientists, software engineers, and product managers to translate business requirements into technical solutions.
Build and maintain scalable ML pipelines using MLOps tools and practices.
Develop APIs and microservices to serve models and enable real-time inference.
Ensure high performance, reliability, and security of AI applications in production.
Mentor junior engineers and foster a culture of innovation and technical excellence.
Stay current with emerging AI technologies and industry trends.