Engineering Assistant

FEV North America Inc•Auburn Hills, MI

13d

About The Position

Develop and deploy AI-based solutions to automate engineering and business workflows, improving efficiency, decision-making, and productivity. Identify opportunities to replace manual or rule-based processes with intelligent AI-driven workflows and agents. Design, develop, and integrate machine learning (ML), reinforcement learning (RL), and generative AI models for engineering applications. Replace conventional rule-based control algorithms and physics-based functions with data-driven ML/RL models where appropriate. Develop data pipelines for collection, cleaning, feature engineering, training, validation, and deployment of AI models. Train, optimize, and validate ML/RL models using simulation, test, and field data. Collaborate with controls, software, systems, and domain experts to integrate AI models into production systems. Support development of digital twins, predictive analytics, anomaly detection, optimization, and intelligent decision-making systems. Monitor model performance, perform retraining activities, and ensure robustness and scalability of deployed solutions. Prepare technical reports, documentation, presentations, and demonstrations for internal and customer stakeholders. Stay current with emerging AI technologies, frameworks, and best practices and evaluate their applicability to engineering challenges.

Requirements

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, Data Science, Artificial Intelligence, or a related field
Strong understanding of Machine Learning, Deep Learning, Reinforcement Learning, and Generative AI concepts
Proficiency in Python and common AI/ML frameworks such as TensorFlow, PyTorch, and RL libraries
Experience with data processing, feature extraction, model training, validation, and deployment workflows
Knowledge of optimization techniques, control systems, and system modeling concepts
Experience with software development tools, version control systems, and CI/CD processes
Strong analytical and problem-solving skills with the ability to work on complex engineering challenges
Professional communication skills (oral and written) and ability to present technical concepts to diverse audiences
Self-motivated team player capable of working in a fast-paced, multidisciplinary development environment

Nice To Haves

Familiarity with cloud-based AI platforms and MLOps practices is preferred

Responsibilities

Develop and deploy AI-based solutions to automate engineering and business workflows, improving efficiency, decision-making, and productivity
Identify opportunities to replace manual or rule-based processes with intelligent AI-driven workflows and agents
Design, develop, and integrate machine learning (ML), reinforcement learning (RL), and generative AI models for engineering applications
Replace conventional rule-based control algorithms and physics-based functions with data-driven ML/RL models where appropriate
Develop data pipelines for collection, cleaning, feature engineering, training, validation, and deployment of AI models
Train, optimize, and validate ML/RL models using simulation, test, and field data
Collaborate with controls, software, systems, and domain experts to integrate AI models into production systems
Support development of digital twins, predictive analytics, anomaly detection, optimization, and intelligent decision-making systems
Monitor model performance, perform retraining activities, and ensure robustness and scalability of deployed solutions
Prepare technical reports, documentation, presentations, and demonstrations for internal and customer stakeholders
Stay current with emerging AI technologies, frameworks, and best practices and evaluate their applicability to engineering challenges