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Mid-level ML/AI role, metro location, and generalist AI requirements attract strong applicant competition.
Requires mining-domain expertise combined with ML/AI and document-intelligence skills, making cross-industry transfer difficult.
Role demands niche mining domain experience plus specific AI, document-intelligence, graph and Azure skills, raising screening rigor.
Develop and implement AI-driven automation and analytics workflows for mining engineering, integrating diverse data sources for enhanced decision-making and operational productivity.
Build scalable AI solutions including document intelligence, machine learning models for predictive analytics, and knowledge graph-based systems for global mining projects.
Collaborate with multidisciplinary teams worldwide to deliver, document, and maintain AI applications aligned with mining engineering requirements using Azure cloud technologies.
Bachelor's or Master's degree in Mining Engineering, Computer Science, Data Science, AI, Software or Geotechnical Engineering.
Experience developing AI, machine learning, automation, or data analytics solutions in mining, engineering, infrastructure, or asset-intensive domains.
Proficiency in Python and hands-on experience with AI/ML libraries, large language models, OCR, computer vision, and Azure AI services.
Work Experience Required: Not explicitly mentioned in the JD.
Strong integration of mining domain expertise with advanced AI, automation and data engineering skills to create practical, scalable solutions.
Experienced in end-to-end AI project delivery including model development, deployment, monitoring, and collaboration with engineering and data science teams.
Comfortable communicating complex AI technical concepts to diverse stakeholders and working across global multidisciplinary teams in a structured delivery environment.