Engineering Assistant

Description

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