Vale
From Vale's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
Success in this role will be demonstrated through your ability to: Deliver scalable AI and machine learning solutions that generate measurable business value.
You are an innovative and technically accomplished AI professional who thrives at the intersection of advanced analytics, engineering, and business transformation. You enjoy solving complex problems, collaborating with multidisciplinary teams, and driving meaningful operational improvements through technology. Success in this role will be demonstrated through your ability to: Deliver scalable AI and machine learning solutions that generate measurable business value. Collaborate effectively with technical and operational stakeholders across global environments. Lead innovation initiatives and evaluate emerging technologies for business impact. Balance technical excellence with practical business outcomes. Drive responsible AI adoption while maintaining strong governance and security practices. Influence decision-making through advanced analytics and predictive insights. Mentor team members and contribute to a culture of continuous learning and innovation. Bachelor's Degree in Computer Science, Data Science, Engineering, or a related discipline. Master's Degree in Engineering, Computer Science, Data Science, Artificial Intelligence, or a related field is preferred 11 to 15 years of relevant experience in artificial intelligence, machine learning, advanced analytics, software engineering, or related fields. Proven experience developing and deploying enterprise-scale machine learning solutions. Strong experience with MLOps, cloud-native AI platforms, and machine learning lifecycle management. Experience working with industrial, operational technology (OT), IoT, or manufacturing data environments is highly desirable. Demonstrated success delivering AI solutions that drive operational performance and business outcomes. Deep expertise in machine learning, Generative AI, Agentic AI, and advanced analytics. Strong proficiency with PyTorch, TensorFlow, Azure Machine Learning, MLflow, Docker, Kubernetes, and related technologies. Experience optimizing AI models using GPU acceleration technologies such as CUDA and TensorRT. Knowledge of enterprise data architectures, cloud infrastructure, Infrastructure as Code, and DevOps practices. Familiarity with Microsoft Copilot, SAP Joule, and AI-enabled business solutions. Strong understanding of data governance, privacy regulations, security practices, and ethical AI principles. Excellent communication and stakeholder management skills. Ability to lead cross-functional initiatives and influence technical strategy. Strong problem-solving, analytical, and organizational capabilities. Design, develop, deploy, and optimize advanced machine learning models for industrial use cases such as predictive maintenance, geohazard detection, ore grade optimization, and equipment failure prediction. Ensure models are production-ready and aligned with business objectives and operational requirements. Build and maintain robust MLOps pipelines using Azure Machine Learning, MLflow, Docker, and Kubernetes. Automate model deployment, monitoring, retraining, and lifecycle management processes. Implement edge AI solutions that enable real-time inference and decision support in remote mining environments. Evaluate emerging technologies and identify opportunities to enhance automation, productivity, and knowledge management across the organization. Contribute thought leadership and technical direction for future AI initiatives. Ensure responsible AI adoption through governance frameworks, ethical AI practices, and compliance with global privacy and security requirements. Support data integrity, cybersecurity, role-based access controls, and enterprise AI governance standards. Promote secure and compliant use of AI technologies across business functions. Contribute to strategic decision-making through predictive analytics and data-driven insights.
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