Research Scientist - Machine Learning

Roles and responsibilities

• Develop innovative algorithms and methodologies in artificial intelligence and machine learning (AIML) tailored for process and product development.
• Analyse extensive datasets to identify patterns, trends, and insights, focusing on diagnostics and prognostics for large-scale energy equipment.
• Implement and enhance AIML algorithms and models for optimal performance.
• Design and execute experiments to evaluate the efficacy and reliability of AIML-based solutions.
• Document research findings, methodologies, and implementation details for effective knowledge sharing and future reference.
• Collaborate with cross-functional teams, including engineers, researchers, and product managers, to integrate AIML solutions into existing system platforms.
• Stay informed on advancements in AIML, control systems, and signal processing engineering through literature reviews and participation in relevant conferences and seminars.
• Research, conceptualize, and develop AI solutions for complex industrial challenges.
• Work collaboratively with fellow researchers on ongoing and new projects.
• Demonstrate the value of AI through early prototypes and solutions addressing real-world problems.
• Utilize software libraries, tools, and practices to implement efficient, scalable, and reusable solutions.
• Contribute to intellectual property development by writing invention disclosures and filing patents.
• Publish research in scientific journals and present findings at conferences.

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 and NumPy.
• 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.