Lead Research Engineer - AIML

Roles and Responsibilities

• Lead the development of advanced algorithms and methodologies in artificial intelligence and machine learning (AIML) to drive process and product
• Lead the analysis of extensive datasets to identify complex patterns, trends, and insights, with an emphasis on diagnostics and prognostics for large-scale energy equipment.
• Develop and optimize AIML algorithms and models to ensure superior performance and scalability.
• Design, conduct, and supervise experiments to assess the efficacy and reliability of AIML-based solutions.
• Document and disseminate research findings, methodologies, and implementation strategies for effective knowledge sharing and future reference.
• Collaborate with and guide cross-functional teams, including engineers, researchers, and product managers, to seamlessly integrate AIML solutions into existing system platforms.
• Stay at the forefront of advancements in AIML, control systems, and signal processing engineering through literature reviews and active participation in conferences and seminars.
• Lead research initiatives to conceptualize and develop AI solutions for complex industrial challenges.
• Demonstrate the impact of AI through advanced prototypes and solutions that address real-world problems.
• Utilize and advocate for best practices in software libraries, tools, and methodologies to implement efficient, scalable, and reusable solutions.
• Drive intellectual property development by authoring invention disclosures and filing patents.
• Publish research in high-impact scientific journals and present findings at leading conferences.

Required Qualifications

• PhD with 3-7 years relevant experience or Masters with 6 -10 years relevant experience from a reputed institution.
• Extensive understanding and experience in machine learning, artificial intelligence, and related fields.
• Proven track record of applying multiple advanced AIML concepts to practical applications.
• Proficiency in programming languages and frameworks commonly used in AIML applications, such as Python, TensorFlow, PyTorch, and others.
• Expertise in data analysis and manipulation using tools like pandas, NumPy, and proficiency in software development best practices, including version control (e.g., Git) and agile methodologies.
• Strong leadership capabilities, excellent problem-solving skills, and ability to think critically and creatively.
• Superior communication skills and ability to lead, mentor, and work effectively in a collaborative team environment.
• Demonstrated ability to build advanced prototypes and rapidly develop proof-of-concepts to illustrate solution feasibility.