Senior Machine Learning Engineer (Computer Vision & AI)

FORVIA; Auburn Hills (MI); On-site; USD 100,000 - 130,000; Full time

Job summary

FORVIA is seeking a Senior Machine Learning Engineer to drive innovation in automotive products. You will develop and deploy advanced AI solutions focusing on computer vision and predictive analytics.

This role requires hands-on experience in machine learning, excellent Python skills, and the ability to work on complex problems in a cross-functional team environment. Successful candidates will have a Master's or PhD in a related field and extensive ML experience.

Qualifications

• 5+ years of experience in machine learning or applied AI roles.
• Strong expertise in machine learning and deep learning, especially in computer vision.
• Practical experience with building and deploying models in production.

Responsibilities

• Design and deploy machine learning models focused on computer vision and predictive maintenance.
• Build end-to-end ML pipelines and optimize model performance.
• Collaborate with cross-functional teams to translate problems into AI solutions.

Skills

Machine learning

Deep learning

Python

Computer vision

Predictive analytics

Cloud platforms (Azure)

Education

Master’s or PhD in Computer Science or related field

Tools

PyTorch

TensorFlow

CUDA

Job description

As a Senior Machine Learning Engineer, you will play a key role in developing and deploying advanced AI solutions that drive innovation across our automotive products and manufacturing processes. This role is focused on applied machine learning, with an emphasis on computer vision, predictive analytics, and scalable model deployment.

You will partner with cross-functional teams across engineering, manufacturing, and R&D to design, build, and productionize machine learning models that deliver measurable business impact. This is a hands‑on role requiring strong technical depth, ownership of model lifecycle, and the ability to operate effectively in a fast‑paced, evolving environment.

Key Responsibiliti

• Design, develop, and deploy machine learning models with a focus on computer vision, predictive maintenance, and anomaly detection
• Build and maintain end‑to‑end ML pipelines, including data preprocessing, model training, valuation, and deployment
• Collaborate with engineering, manufacturing, and business stakeholders to translate real‑world problems into scalable AI solutions
• Optimize model performance and scalability using GPU acceleration and parallel computing frameworks
• Leverage Python and deep learning frameworks (PyTorch, TensorFlow) to implement production‑ready solutions
• Partner with data and software engineering teams to integrate models into production systems and workflows
• Contribute to AI innovation initiatives, including exploration of generative AI use cases in design and engineering contexts
• Ensure best practices in model reproducibility, documentation, and performance monitoring
• Stay current with advancements in machine learning and apply relevant techniques to improve existing capabilities

Your Profile & Competenc

• Master’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field
• 5+ years (preferably 7+) of hands‑on experience in machine learning or applied AI roles
• Strong expertise in machine learning and deep learning, with practical experience in computer vision applications
• Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow
• Experience building and deploying models in production environments
• Familiarity with GPU acceleration (CUDA or similar frameworks) and performance optimization techniques
• Experience with ML pipelines, model lifecycle management, and scalable system design
• Ability to work effectively in matrixed, cross‑functional environments
• Strong problem‑solving and analytical skills, with the ability to translate complex data into actionable insights
• Effective communicator, able to explain technical concepts to non‑technical stakeholders
• Experience in automotive, manufacturing, or industrial environments is a strong plus
• Familiarity with cloud platforms (e.g., Azure) and Agile development practices is preferred

What Success Looks

• Delivering production‑ready ML solutions that drive measurable improvements in efficiency, quality, or innovation
• Building scalable, maintainable pipelines and models used across the organization
• Acting as a trusted technical partner to both engineering and business stakeholders
• Contributing to the advancement of AI capabilities within the organization