AI Development Lead for New Materials, the Leading Mining and Metallurgical Company

AI Development Lead for New Materials, the Leading Mining and Metallurgical Company Russia The person will lead the establishment and implementation of the AI function across the entire lifecycle of developing new inorganic materials and alloys — from analyzing scientific ideas and hypotheses to generating new compounds, modeling material properties, and planning experiments. Responsibilities: • Update and execute the long-term strategy for implementing AI tools across the full lifecycle of developing new inorganic materials and alloys — from idea discovery to the generation of new compounds and experiment planning — in line with global best practices. • Develop the annual roadmap and oversee the delivery of projects focused on creating and implementing advanced models based on: - large language models (for scientific publication analysis, project concept generation, synthesis planning and verification, research, and testing); - predictive and generative AI (for the development of an AI platform for modeling and generating new materials based on platinum group metals). • Actively participate in projects, manage the internal team, and identify and supervise external contractors and partners. • Develop and align the department budget and KPI system. • Engage with external expert networks and represent the company at Russian and international industry events. Requirements: • Higher education in computer science, applied mathematics, computational modeling, machine learning, physics, chemistry, materials science, or related fields . • Proven hands-on experience in developing, adapting, or implementing solutions based on generative, predictive, and/or multimodal AI for applied business, scientific, or R&D use cases. • Experience bringing AI/ML solutions into real-world operation: from problem definition and data strategy development to achieving measurable outcomes and integration into business processes. • Strong understanding of modern AI approaches, including large language models, generative models for science and materials discovery, property prediction methods, materials candidate search, and AI-assisted scientific research. • Ability to critically assess the applicability of AI approaches, understand their limitations, and select realistic use cases for specific scientific and technological challenges. • Significant advantage: experience working at the intersection of AI and natural science/engineering domains such as materials science, chemistry, condensed matter physics, computational chemistry, computational materials science, or related areas. • Basic or advanced understanding of thermodynamics, kinetics, materials modeling, and the relationships between composition, structure, properties, and manufacturing technology. • Experience working with scientific data, publications, computational and experimental results, as well as understanding the specifics of dataset creation in research environments. • Ability to collaborate effectively with researchers, engineers, ML specialists, IT teams, and external partners simultaneously. Contact: d.ustimenko@peers.career Telegram: @dariaust For more job opportunities visit peers.career #jobopportunity #Metallurgy #AI