**Introduction** Hiring manager and Recruiter should collaborate to create the relevant verbiage. **Your role and responsibilities** Seeking new possibilities and always staying curious, we are a team dedicated to creating the world’s leading AI-powered, cloud-native software solutions for our customers. Our renowned legacy creates endless global opportunities for our IBMers, so the door is always open for those who want to grow their career. IBM’s product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive **Required technical and professional expertise** Machine Learning and Deep Learning: Develop and implement machine learning and deep learning models to address business challenges. ML-Ops / AI-Ops: Demonstrate expertise in ML-Ops / AI-Ops practices to ensure efficient model deployment and management. Big Data Management: Manage big data infrastructure and execute data engineering tasks for efficient data processing. Version Control and Collaboration: Utilize version control systems like Git for maintaining codebase integrity and fostering collaboration. AI-Driven Product Development: Design, create, and support AI-driven products to deliver impactful solutions aligned with user needs and business objectives. **Preferred technical and professional experience** Hiring manager and Recruiter should collaborate to create the relevant verbiage. IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.