Job Description SummaryArtificial Intelligence and Machine Learning (AIML) engineer is a entry-level engineer, who will work on building grid innovation applications using model-to-code, and develop systems to validate and verify proof-of-concepts of the AIML application. The AIML engineer works in close collaboration with GA’s Monitoring and Diagnostics (M&D) team, program managers and other GA functions.
This role will also be responsible for building the data analytics applications and work closely with other functions across Grid Automation (GA) business to identify areas where the business can leverage data and data analytics to drive efficiency, increase customer satisfaction, and develop POCs to solve critical problems for our customers.Job Description
Essential Responsibilities
The AIML engineer is responsible for:
Demonstrate novel & transformational applications/analytics to drive innovation & differentiation.
Define the framework to collect, structure and use of databases for AI, to extract value.
Develop AI/ML application to build differentiated products and solutions; with ability to work on customers value-driven applications/analytics to drive innovations.
Design and deploy high-quality, scalable, and secure AI/ML models and applications on the M&D platform, using native or container or microservices principles.
Develop and implement strategies for optimizing the performance and scalability of machine learning models in production.
Collaborate with product management, R&D, and other functions in to understand their needs and develop innovative solutions. Implement and maintain data pipelines for AI/ML models. Monitor and optimize the performance of AI/ML models in production.
Collaborate with cross-functional teams.
Qualifications/Requirements
Master’s/PhD Degree in computer science, Information technology (IT), electrical engineering, or electric power engineering, specifically in the computer and electric power engineering field with hands-on experience in data science.
Experience of working in professional working environment and knowledge of Statistical techniques, artificial intelligence (AI) and machine learning (ML), including, unsupervised learning, supervised learning, and reinforcement learning, Deep learning, large language models (LLMs).
Understanding related to power system protection and automation, monitoring and diagnostics.
Proven experience in applying AI/ML frameworks/workflows.
Understanding MLOps principles.
Able to share ideas and work well in a team environment, proactive approach to tasks displaying initiative.
Flexible and adaptable; open to change and modification of tasks, working in multi-tasking environment.
