The Role
Designs, deploys, and supports AI/ML solutions for engineering applications while administering and implementing EPM/Hyperion and PLM systems. Leads integration, MLOps pipelines, model monitoring, and cross-team coordination, and supports testing, documentation, and continuous improvement of enterprise engineering workflows.
Summary Generated by Built In
Job Overview:
The AI/ML Developer for Engineering IT is responsible for designing, integrating, deploying, and supporting AI/ML solutions that enhance engineering applications, enterprise platforms, and digital workflows. This role focuses on translating business and engineering requirements into scalable, secure, and production-ready AI capabilities, while enabling responsible AI adoption, operational reliability, and continuous improvement across Engineering IT systems.
ResponsibilitiesKey Tasks and Responsibilities:
- Support the deployment, integration, and lifecycle management of AI/ML solutions within Engineering IT platforms, engineering applications, and enterprise workflows
- Collaborate with engineering application owners, business stakeholders, infrastructure teams, and vendors to identify, design, and implement AI-enabled use cases that improve engineering productivity, quality, and operational efficiency
- Develop and maintain production-ready pipelines for model deployment, monitoring, retraining, and version control, following MLOps and DevOps best practices
- Ensure secure, scalable, and reliable integration of AI/ML services with enterprise systems, databases, APIs, and cloud or on-premises environments
- Establish processes for model performance monitoring, drift detection, incident resolution, and continuous improvement to ensure stable business operations
- Work closely with data, cybersecurity, architecture, and compliance teams to ensure responsible AI adoption, data governance, privacy, and adherence to enterprise standards
- Prepare technical documentation, support materials, and knowledge transfer artifacts for Engineering IT teams, end users, and support personnel
- Provide application support and troubleshooting for AI/ML-enabled engineering solutions, including issue analysis, root cause identification, and coordination of fixes with relevant teams
- Contribute to evaluation of emerging AI tools, frameworks, and engineering technology platforms to recommend practical solutions aligned with Engineering IT strategy
- Participate in cross-functional projects, pilot programs, and digital transformation initiatives to drive adoption of AI capabilities across engineering and project delivery functions
Essential Qualifications and Education:
- 2–5 years of hands-on experience in AI/ML development, deployment, or integration, with exposure to production environments
- Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Mathematics, or a related discipline
- Strong programming capability in Python, with practical knowledge of machine learning libraries and frameworks
- Solid understanding of machine learning concepts, model development lifecycle, model evaluation, and performance tuning
- Experience integrating AI/ML solutions with enterprise or engineering applications using APIs, services, and system interfaces
- Working knowledge of MLOps and DevOps practices, including version control, CI/CD, model deployment, monitoring, and retraining workflows
- Familiarity with cloud and on-premises deployment environments, containerization, and scalable solution architecture
- Understanding of data pipelines, data quality, and governance requirements for enterprise AI implementations
- Awareness of AI security, privacy, compliance, and responsible AI practices in enterprise settings
- Strong analytical, problem-solving, documentation, and communication skills, with the ability to collaborate effectively across business, engineering, and IT teams
- Exposure to engineering systems (2D/3D applications provided by AVEVA, HEXAGON, Bentley, Autodesk, others) digital engineering platforms, or enterprise application support will be an added advantage
#LI-NS1 #DICE
About Us Our ingenuity fuels daily life. Together, we’ve forged some of the most trusted partnerships across the energy value chain to make what was once just an idea a reality: laying subsea infrastructure thousands of feet below sea level, installing platforms hundreds of miles from shore, using our expertise to design and build offshore wind infrastructure, and reshaping the onshore landscape to deliver the energy products the world needs safely and sustainably.
For more than 100 years, we've been making the impossible possible. Today, we're driving the energy transition with more than 30,000 of the brightest minds across 54 countries.
For more than 100 years, we've been making the impossible possible. Today, we're driving the energy transition with more than 30,000 of the brightest minds across 54 countries.
Skills Required
- Bachelor's degree in Engineering, Computer Science, or related field
- Minimum 5+ years of experience in IT supporting EPCI business applications as a lead or administrator
- Experience and understanding of Accounting (P&L, BS, Cash Flow)
- Strong finance and accounting background with track record in administering and implementing EPM/Hyperion projects in large environments
- Hands-on experience supporting Hyperion Planning (on-prem) and implementing EPBCS/Oracle EPM
- Strong hands-on experience configuring, deploying, and developing solutions on 3DEXP Platform 201X and/or Enovia V6 and corresponding modules
- Experience with Dassault PLM Enovia 3D Experience 2017
- 2-5 years of hands-on experience in AI/ML development, deployment, or integration in production environments
- Strong programming capability in Python
- Solid understanding of machine learning concepts, model lifecycle, evaluation, and performance tuning
- Experience integrating AI/ML solutions with enterprise applications using APIs and system interfaces
- Working knowledge of MLOps and DevOps practices including version control, CI/CD, model deployment, monitoring, and retraining workflows
- Familiarity with cloud and on-premises deployment environments and containerization
- Understanding of data pipelines, data quality, and governance requirements for enterprise AI
- Awareness of AI security, privacy, compliance, and responsible AI practices
- Strong communication, presentation, documentation, analytical, and problem-solving skills
- Exposure to engineering systems (AVEVA, HEXAGON, Bentley, Autodesk) or digital engineering platforms
- Advanced education (MBA or other master's level education)
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The Company
What We Do
McDermott is a premier, fully-integrated provider of engineering and construction solutions to the energy industry. Our customers trust our technology-driven approach to design and build infrastructure solutions to responsibly transport and transform oil and gas into the products the world needs today. From concept to commissioning, our expertise and comprehensive solutions deliver certainty, innovation and added value to energy projects around the world. It is called the “One McDermott Way.” Operating in over 54 countries, McDermott’s locally-focused and globally-integrated resources include approximately 40,000 employees, a diversified fleet of specialty marine construction vessels and fabrication facilities around the world. To learn more, visit www.mcdermott.com.
