
Engineering Assistant- AI Based Solutions
FEV North America · Auburn Hills, MI
All reasons
- Open 87 days
In its favour
- Still listed on the employer's own board
- 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
- Working towards Bachelor’s or master’s degree in computer science, Electrical Engineering, Mechanical Engineering, Robotics, Data Science, Artificial Intelligence, or a related field
- 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 software development tools, version control systems, and CI/CD processes
- Experience with data processing, feature extraction, model training, validation, and deployment workflows
Preferred Qualifications
- Knowledge of optimization techniques, control systems, and system modeling concepts
- Familiarity with cloud-based AI platforms and MLOps practices is preferred
- 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
Equal opportunity employer as to all protected groups, including protected veterans and individuals with disabilities
Skills
- Machine Learning
- Generative AI
- Deep Learning
- Python
- TensorFlow
- PyTorch
- MLOps
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