Senior Data & AI Specialist

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Requirements:

• English level: C1.
• Bachelor's degree in Engineering, Economics, Mathematics, Physics, or related fields.
• Minimum of 3 years of experience in Artificial Intelligence, Machine Learning, and data automation solutions.
• Advanced proficiency in Python for data analysis, Generative AI, and Machine Learning.
• Strong statistical foundation with high analytical and numerical capabilities.
• Experience developing and deploying AI models in production.
• Knowledge of structured and unstructured databases, including Advanced SQL, NoSQL, and vector databases for embeddings and information retrieval.
• Expertise in AI architectures and tools, including: Machine Learning Frameworks: TensorFlow (Keras), PyTorch, NLP & LLMs: OpenAI API, Hugging Face, LangChain, Retrieval-Augmented Generation (RAG) techniques for improved AI responses
• Proficiency in data visualization tools and dashboard creation.
• Intermediate Excel skills.

Responsibilities:

• Design and improve AI models and behavioural simulations, ensuring accuracy and adaptability across different scenarios.
• Implement and optimize autonomous AI agents for task automation and advanced insight generation.
• Explore different Machine Learning and Generative AI approaches, including reinforcement learning, supervised learning, and unsupervised learning.
• Apply fine-tuning and transfer learning to adapt models to diverse use cases.
• Define and develop strategies for integrating AI into various products and business solutions.
• Collaborate with product and engineering teams to translate AI capabilities into actionable functionalities.
• Develop customization mechanisms to adapt AI models for different industries and customer needs.
• Evaluate and define KPIs to measure and improve model performance
• Design and execute data collection, processing, and validation strategies to enhance model accuracy.
• Integrate Retrieval-Augmented Generation (RAG) techniques to ensure generated responses are contextually relevant and verifiable.
• Apply predictive modeling and simulation techniques to anticipate trends and behaviors.
• Validate model accuracy and consistency through comparisons with real data and reference models.
• Implement dynamic adjustments and optimization of Language Models (LLMs) for improved adaptability across various contexts.
• Work with technical teams to optimize data pipelines and ensure AI models are scalable and efficient in production.
• Develop methodologies for the validation, updating, and continuous improvement of AI models.
• Design interactive dashboards and reports to visualize trends, predictions, and AI model results.
• Present findings and recommendations to key stakeholders, ensuring alignment with strategic business objectives.