Roles and responsibilities

• Develop novel AIML algorithms and methodologies applicable to control systems engineering and anomaly detection problems.
• Analyse large time series datasets to identify patterns, trends, and insights to deliver algorithms dealing with diagnostics and prognostics of large energy equipment.
• Implement and optimize AIML algorithms and models.
• Design and conduct experiments to test the performance and robustness of AIML-based solutions.
• Document research findings, methodologies, and implementation details for knowledge sharing and future reference.
• Collaborate with cross-functional teams, including engineers, researchers, and product managers, to integrate AIML solutions into existing system platforms.
• Keep abreast of the latest advancements in AIML, control systems, and signal processing engineering through literature review and participation in relevant conferences and seminars.

Required Qualifications

• PhD with 2 - 5 Years Experience or Master’s degree with 5 - 7 Years Experience from a reputed institution in Computer Science or other engineering field.
• Strong understanding of fundamental concepts in statistics, machine learning, and artificial intelligence.
• Proficiency in programming languages commonly used in AIML applications such as Python, PySpark, PyTorch, Pandas, or similar.
• Experience with data analysis and manipulation using tools like Pandas, NumPy, or MATLAB. Familiarity with software development best practices, including version control (e.g., Git) and agile methodologies.
• Basic knowledge of cloud-based architectures
• Excellent problem-solving skills and ability to think critically and creatively.
• Strong communication skills and ability to work effectively in a collaborative team environment.
  • Demonstrated ability to build prototypes and quickly develop proof of concepts to show solution feasibility.