This role requires close collaboration with product managers and stakeholders to identify AI-driven use cases and translate them into scalable, actionable features. The candidate will be responsible for architecting and deploying AI applications into existing software ecosystems, ensuring seamless integration through APIs and microservices
A solid foundation in machine learning techniques, data structures, and algorithms is essential, along with hands-on experience in evaluating model performance, debugging technical issues, and driving continuous improvements. Familiarity with cloud platforms such as AWS, Google Cloud, or Azure for model deployment and scalability is required
Proficiency with AI frameworks and libraries like TensorFlow, PyTorch
Proficiency in Python
Should be able to perform supervised fine-tuning or reinforcement learning when base models require domain-specific improvements
Partner with product managers and stakeholders to identify AI use cases and translate them into actionable features
Deploy AI applications into existing software systems and ensure seamless integration using APIs and microservices
Solid understanding of machine learning techniques, data structures, and algorithms
Familiarity with cloud platforms (AWS, Google Cloud, or Azure) for model deployment and scalability
Knowledge of data analysis, big data, and statistical concepts
Evaluate the performance and efficiency of AI systems, debug technical issues, and implement enhancements for continuous improvement
APIs and Integration: Familiarity with integrating external APIs and building custom interfaces
Should have knowledge of integrating HANA DB with
AIShould be familiar with consuming SAP APIs in AI