Data Scientist / Machine Learning Engineer

CorTech is seeking a Data Scientist / Machine Learning Engineer to develop and deploy AI and deep learning solutions for the automotive industry. This onsite role in Auburn Hills, MI focuses on building models for computer vision, predictive maintenance, anomaly detection, and generative AI use cases, working closely with cross-functional partners.

Responsibilities

• Design, develop, and deploy AI models for complex automotive problems, including computer vision and generative AI.
• Partner with cross-functional teams to understand business challenges and identify opportunities to apply machine learning.
• Use generative AI models to support innovation across design, R&D, and manufacturing processes.
• Optimize existing machine learning models for performance and scalability using CUDA advanced GPU architectures and parallel computing frameworks for efficient computation.
• Design and implement machine learning pipelines for data preprocessing, model training, and evaluation using performance metrics.
• Implement machine learning solutions using Python and deep learning frameworks including PyTorch and TensorFlow.
• Apply statistical methods and machine learning algorithms to solve complex problems within the automotive domain.
• Keep current on advances in data science, machine learning, deep learning, and AI, and apply new approaches to drive continuous innovation.
• Develop and maintain documentation for data analysis methods, model development, and deployment processes to support reproducibility and compliance with industry standards.

Requirements

• PhD or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Minimum 5 years of experience in a machine learning engineering role, preferably in automotive or a related sector.
• Proven experience in machine learning, deep learning, and AI, including developing and deploying models for real-world applications.
• Strong understanding of Python, CUDA, and GPU architectures for parallel computing and model optimization.
• Solid knowledge of machine learning architectures and techniques, with a focus on computer vision and generative AI.
• Proficiency with deep learning frameworks such as PyTorch and TensorFlow.
• Experience with parallel computing and optimization for high-performance computing environments.
• Ability to collaborate with teams and communicate complex concepts clearly to non-technical stakeholders.
• Strong analytical skills to interpret complex data and convert findings into strategic insights and practical solutions.
• Self-motivated approach with a commitment to continuous learning and professional development.
• Experience working in Agile and with a cloud provider such as Azure is a plus.

Technologies

• Python
• CUDA
• PyTorch
• TensorFlow
• CUDA advanced GPU architectures
• Parallel computing frameworks
• Agile
• Azure

Location and Work Setting

Auburn Hills, MI (onsite)