Data Scientist

PwC Israel · telaviv

Our mission is to build and maintain cutting-edge technological infrastructures that empower innovation in the fields of data and artificial intelligence. Join us to lead the development of scalable, next-generation platforms that enable meaningful transformation and impact. We are looking for an Data Scientist to join our NLP team. The role combines research, model development, and hands-on engineering, spanning from training and evaluating large language models to building AI-powered applications and production systems. The ideal candidate is someone who can take ownership of complex problems, independently explore new approaches, and turn research ideas into impactful, real-world AI solutions. Role Overview Develop cutting-edge research and engineering solutions in Large Language Models (LLMs) and Generative AI. Work across the full lifecycle of foundation model development — from research and experimentation to scalable training and production infrastructure. Develop advanced LLM solutions and AI-powered applications, including chatbots, agents, and other GenAI systems using modern AI APIs and frameworks. Key Responsibilities Conduct applied research on LLM training methodologies, optimization, and evaluation. Train, fine-tune, and evaluate large-scale language models. Design experiments and domain-specific benchmarks to measure model performance and behavior with statistically rigorous evaluations. Monitor and analyze the behavior and performance of AI models and agents. Build and maintain infrastructure for distributed training and large-scale experimentation. Develop ML models and AI applications in Python and integrate them with modern agent-based systems. Collaborate with researchers and engineers to transform research ideas into production-ready solutions. Continuously evaluate new research and implement state-of-the-art techniques across a wide range of domains, including healthcare, defense, finance, government, and more. Requirements Requirements 4+ years of experience in ML, Data Science, or AI Engineering. Hands-on experience training and fine-tuning large neural networks. Hands-on experience with modern LLM technologies, including RAG, SFT, RLHF/DPO, and high-performance inference frameworks (e.g., vLLM). Experience with GPU-based training environments and large-scale ML infrastructure. Strong Python and software engineering skills, including experience developing ML models, production AI systems and modern LLM/agent frameworks and APIs (e.g. PyTorch, Hugging Face, CUDA, vLLM, LangChain) Strong analytical and research skills, with the ability to independently investigate and solve complex problems. Self-driven, highly motivated, and able to take ownership of challenging projects.

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