AI/ML Engineer

As an AI Engineer passionate about Generative AI and AI-assisted modernization, you will be responsible for developing cutting-edge solutions to drive innovation within the organization. Your primary focus will be on designing and developing in-house GenAI applications, collaborating with vendors to implement proof of concepts (POCs) for complex AI solutions, and aiding in the modernization of legacy systems through AI-driven automation. Your key responsibilities will include: - Designing and developing in-house GenAI applications tailored to internal use cases. - Collaborating with vendors to evaluate and implement POCs for advanced AI solutions. - Working on AI-powered tools to modernize Software Development Life Cycle (SDLC) and migrate code from legacy to modern technologies. - Providing technical support, training, and AI adoption strategies for internal users and teams. - Assisting in integrating AI solutions into software development processes. To excel in this role, you must have: - A Bachelor's or Master's degree in Computer Science, Computer Engineering, Computer Applications, Information Technology, or a related field in AI/ML. - Relevant certification in AI/ML would be advantageous. - Experience with at least 2 successful AI/ML POCs or production deployments. - Previous involvement in AI-powered automation, AI-based DevOps, or AI-assisted coding. - Demonstrated teamwork and delivery capabilities. - Strong analytical and problem-solving skills with a continuous learning mindset. - A positive attitude with attention to detail. In terms of AI/ML expertise, you should possess: - Proficiency in Python programming. - Hands-on experience with GenAI models and Large Language Models (LLMs/SLMs) in real projects or POCs. - Practical experience in Machine Learning and Deep Learning. - Familiarity with AI/ML frameworks such as PyTorch, TensorFlow, or Hugging Face. - Understanding of MLOps pipelines and AI model deployment. Additionally, familiarity with System Modernization & Enterprise Technologies is beneficial: - Basic knowledge of Java, Spring, React, Kotlin, and Groovy. - Willingness to work on AI-driven migration projects like PL/SQL to Emery or JavaScript to Groovy DSL. - Experience with code quality, AI-assisted code refactoring, and testing frameworks. For Enterprise integration & AI adoption, you should have: - The ability to integrate AI solutions into enterprise workflows. - Experience with API development and AI model integration in applications. - Proficiency in version control and collaboration tools like Git and CI/CD pipelines. While not mandatory, the following would be considered advantageous: - Experience in code migration and modernization projects. - Exposure to third-party AI tools and their adoption in enterprises. - AI-driven development experience for large-scale software applications.,