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Job Description & How to Apply Below
Overview
We are seeking experienced and innovative AI Scientists to join our Asset Management team. This role focuses on developing AI‑powered applications that enhance operations, optimize maintenance strategies, extend asset life, reduce operating costs, and improve equipment safety.
Responsibilities- Design, develop and deploy AI applications to support predictive and preventive maintenance, asset life extension strategies, operational cost reduction, equipment safety and reliability.
- Leverage LLMs and SLMs for intelligent automation and decision support.
- Collaborate with cross‑functional teams to identify AI opportunities.
- Work within Azure cloud environments and integrate with Microsoft Copilot tools.
- Ensure all work complies with company policies, procedures and confidentiality standards.
- Provide structured, timely updates and reports on project progress.
- Explore and evaluate emerging AI technologies and methodologies.
- Demonstrate flexibility in adapting to evolving project needs and priorities.
- Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Engineering, or a related field.
- Minimum of 3 years of experience in AI/ML development, preferably in industrial or asset‑intensive environments.
- Proficiency in programming languages such as Python, R, or similar.
- Experience working with Azure cloud services and AI tools.
- Familiarity with Microsoft Copilot and its integration into enterprise workflows.
- Strong communication skills in English (written and verbal).
- Ability to work independently while maintaining alignment with team goals.
- Willingness to travel internationally as required.
- Adherence to strict confidentiality and data protection standards.
- Structured reporting and documentation practices.
- Collaborative and proactive mindset.
- Commitment to continuous learning and innovation.
- Experience with asset management systems or industrial operations in gas compression and gas processing industry.
- Knowledge of maintenance management frameworks (e.g., RCM, CBM).
- Understanding of data governance, security, and compliance in AI applications.
- Ability to translate business needs into technical solutions.
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