MLOps / Platform Engineer (AKS + CI/CD)
At Fluor, we are proud to design and build projects and careers. We are committed to fostering a welcoming and collaborative work environment that encourages big-picture thinking, brings out the best in our employees, and helps us develop innovative solutions that contribute to building a better world together. If this sounds like a culture you would like to work in, you’re invited to apply for this role.
Job Description
Role Overview
The AIMLOps Engineer will play a key role in enabling Fluor’s AI Office by operationalizing machine learning models across enterprise and project delivery environments. This role focuses on building, deploying, monitoring, and scaling AI & ML solutions that support engineering, construction, project controls, safety, and business operations.
Key Responsibilities
- Design, build, and maintain end‑to‑end MLOps pipelines for model training, validation, deployment, and monitoring
- Productionize ML and AI models using CI/CD, Infrastructure‑as‑Code, and container orchestration best practices
- Implement model registries, experiment tracking, feature management, and data lineage to ensure reproducibility and governance
- Deploy and operate real‑time, batch, and API‑based inference services, including LLM‑powered solutions where applicable
- Monitor model performance, drift, bias, latency, and reliability; define SLAs, alerts, and automated retraining workflows
- Operationalize machine learning and AI models into production environments using CI/CD best practices
- Collaborate with data scientists to transition models from experimentation to scalable, enterprise‑grade solutions
- Implement model versioning, data lineage, and experiment tracking to ensure reproducibility and governance
- Monitor model performance, drift, bias, and reliability; implement automated alerts and retraining workflows
- Develop and maintain infrastructure for ML workloads using cloud and containerized platforms
- Ensure AI solutions meet Fluor’s security, data privacy, and compliance standards
- Support AI use cases across EPC lifecycle phases including engineering, construction, project controls, HSE, and operations
- Document MLOps standards, architecture, and operating procedures for enterprise reuse
- Continuously evaluate new MLOps tools and technologies to improve efficiency and scalability
Basic Job Requirements
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related discipline
- 3–5 years of hands‑on experience in MLOps, DevOps, or production ML environments
- Strong experience deploying and supporting ML models in production
- Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit‑learn)
- Experience with CI/CD pipelines and automation tools
- Solid understanding of software engineering best practices and system design
- Azure Cloud certifications related to ML or DevOps are a plus
Other Job Requirements
Preferred Qualifications
To be Considered Candidates:
Must be authorized to work in the country where the position is located.
We are an equal opportunity employer. All qualified individuals will receive consideration for employment without regard to race, color, age, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, genetic information, or any other criteria protected by governing law.