AIML Engineer

Optimization Methods

• Linear Programming (LP)
• Nonlinear Programming (NLP)
• Mixed-Integer Optimization (MILP)
• Dynamic Optimization
• Gurobi / CPLEX / Pyomo

AI & Machine Learning

• Supervised Learning
• Time-Series Forecasting
• Reinforcement Learning
• Predictive Maintenance
• Hybrid AI-Models

Mathematical Foundation

• Numerical Methods
• Control Theory
• Optimization Algorithms
• Applied Mathematics for Engineering
• Bachelor’s / Diploma / Master's degree / PhD in Process Systems Engineering or Chemical Engineering or Computer Science or similar degrees
• Deep knowledge of Probability, Statistics, and Machine learning algorithms
• Good Understanding of model development (first principle/data-based) and Numerical Analysis Techniques
• Strong proficiency in Python and Shell scripting.
• Solid understanding of software development best practices.
• Knowledge in Containerization, Cloud Architectures, DevOps and MLOps workflows
• Hands-on experience with implementing model, designing concepts, automate systems
• Domain knowledge in EPC, Process engineering and Plant operation would be an advantage

Key Role & Responsibility

• Design and develop robust software solutions for engineering and chemical process applications.
• Research and implement appropriate ML algorithms and tools
• Develop systems for Machine Learning Model Training
• Architect and manage solutions in cloud environments, leveraging DevOps and MLOps methodologies.
• Result oriented, self-starter and able to work independently with minimal guidance.
• Attention to detail and being proactive.
• Involve experts whenever required.
• Ensure high-quality code through rigorous testing, debugging, and optimization.

Soft Skills

• Excellent communication skills with strong proficiency in the English language
• Creative thinking and a proactive approach to problem-solving
• Collaborative spirit with the ability to work effectively in cross-cultural and cross-functional teams
• Strong ownership mindset and accountability for deliverables
• Continuous learning attitude and openness to feedback