Siemens Energy: Data Scientist interview скачать в хорошем качестве

Siemens Energy: Data Scientist interview

Partner with developers in Agile teams to merge LLMs and classical AI into end-user apps, emphasizing user experience and real-time performance. Customize LLMs: Tailor pre-trained models to meet business needs using timely engineering, transfer learning, and few-shot methods. Data Hygiene: Collect, clean, and preprocess large datasets to ensure high-quality input for AI models. Model Validation & Reporting: Measure and validate the performance of AI models using appropriate metrics. Document AI models, algorithms, and processes, and communicate findings and results to stakeholders. Integration: Integrate external knowledge sources including databases, APIs and document repositories to enrich LLM with real time or domain specific information Collaboration: Work with data scientists, software engineers, and product managers to integrate AI solutions into products and services