Applied AI Engineering, Lead
Pubblicato il 15-10-2026 - Deel in Belluno
Overview In this role you will lead a high-performing data science team to deliver impactful ML models and data-driven insights that support Deel’s growth. You will partner with engineering and product teams to deploy analytics in production and mentor junior scientists. You’ll shape the data science roadmap, stay ahead of industry trends, and ensure reproducibility and reliability of models. This is a chance to drive AI-powered decision making at scale in a fast-moving, global company. Retribuzione / Benefits * Stock grant opportunities * Optional flexible working office membership * Competitive total rewards * Role- and location-based perks Responsabilità * Lead and manage a team of data scientists to deliver high-impact data models, algorithms, and insights for various business units * Develop and execute data science projects,
ensuring alignment with business objectives and timely delivery * Guide the team in applying machine learning techniques to solve complex business problems and improve decision-making * Collaborate with engineering and product teams to ensure seamless deployment of data models and analytics into production * Mentor and coach junior data scientists, fostering growth and development within the team * Develop and maintain best practices for data science workflows, ensuring high standards of reproducibility and reliability * Drive innovation by staying updated on industry trends and emerging technologies in data science * Ensure the integrity, accuracy, and scalability of data models and analyses * Communicate data insights and model outcomes to non-technical stakeholders, including leadership teams * Oversee the continuous improvement of data processes, methodologies, and tools within the team Requisiti fondamentali * 5+ years of experience in data science, with a strong background in machine learning, statistics, and data modeling * Strong expertise in LLM engineering: RAG, agents and tool use, fine-tuning, evals, and optimising cost and lat