Data Scientist and LLM Engineer
- תל אביב
- זמנית
- משרה מלאה
- The ideal candidate will bring in-depth technical skills and industry experience to design, develop, and optimize AI/ML models, particularly Large Language Models (LLMs), to address complex challenges in our target sectors ementation in simulation environments.
- Support software, hardware, and firmware teams in implementing algorithms on embedded systems.
- Design, develop, and deploy cutting-edge causal inference and AI models to solve complex problems in user behavior, root cause analysis, gaming and mobile applications domains.
- Develop Python-based solutions for data processing, model training, and deployment in production environments.
- Collaborate with cross-functional teams to integrate AI/ML solutions into enterprise-grade applications.
- Conduct research on the latest advancements in AI, ML, and LLMs to maintain competitive edge.
- Optimize and fine-tune LLMs for performance, scalability, and cost efficiency.
- Analyze and process large datasets to extract actionable insights that drive business value.
- Develop and maintain robust, scalable, and efficient codebases and documentation.
- Be part of a forward-thinking start-up company pushing the boundaries of AI and ML.
- Collaborate with a talented team dedicated to innovation and excellence.
- Opportunities for professional growth and development in cutting-edge technologies.
- Master's or Ph.D. in Computer Science, Electrical Engineering, Mathematics, or a related field.
- 4 + years of professional Python development, designing and implementing end-to-end machine-learning pipelines.
- Practical experience with Generative AI techniques,
- Proven hands-on experience with Large Language Models (LLMs) and Transformer architectures.
- Extensive hands-on experience with NLP frameworks and libraries, such as Hugging Face Transformers, PyTorch, and OpenAI APIs.
- Proven ability to deploy AI/ML models to production, with a focus on scalability and robustness
- Excellent understanding of unstructured and semi-structured data processing methods.
- Experience working in cloud environments (AWS, GCP, or Azure) and leveraging distributed computing frameworks (e.g., Spark or Ray).
Mploy