Senior Data Scientist-AI/ML

About the Team: ZF COE Team is effectively communicate complex technical concepts related to AI, ML, DL, and RL to both technical and non-technical audiences. This might involve presenting research findings at conferences or writing papers for academic journals.

What you can look forward to as Senior Data Scientist (m/f/d):

• Stay at the forefront of the field by keeping abreast of the latest advancements in algorithms, tools, and theoretical frameworks. This might involve researching areas like interpretability of machine learning models or efficient training methods for deep neural networks.
• Conduct cutting-edge research to identify novel AI/ML methodologies, including Deep Learning (DL), Reinforcement Learning (RL), Generative AI and Agentic AI.
• Perform domain-specific data analysis to identify trends, patterns, and insights relevant to business objectives.
• Collaborate with business stakeholders to understand operational challenges and translate them into analytical tasks.
• Fine-tune and optimize existing AI/ML solutions to reduce bias and improve performance, accuracy in alignment with business goals.
• Ensure that the right architecture and design principles are consistently applied to achieve security, scalability, and long-term sustainability.
• Validate model outputs and ensure they are interpretable, reliable, and actionable for decision-making.
• Effectively communicate complex technical concepts related to AI, ML, DL, and RL to both technical and non-technical audiences. This might involve presenting research findings at conferences or writing papers for academic journals.

Your profile as Senior Data Scientist (m/f/d):

• 8+ years of experience in research development, with a strong understanding of data structures and algorithms.
• Master's degree in Mathematics, Computer Science or other related technical fields. PhD is good to have.
• Hands-on experience with generative AI architectures including GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and autoregressive models, Transformer-based networks, LLMs, SLMs including model finetuning.
• Familiar with implementing RAG (Retrieval-Augmented Generation) architecture for sophisticated AI applications
• Basic knowledge of AI accelerator chips
• Knowledge of MLOps practices to ensure the robustness, reliability and scalability of AI systems
• Strong Python programming skills and experience with modern AI frameworks