Company Overview:
Dar, the founding member of the Sidara group, is an international multidisciplinary consulting organization specializing in engineering, architecture, planning, environment, project management, facilities management, and economics. Sidara operates in 60 countries with 20,500 professionals, Dar connects people, places, and communities through innovative solutions to the world's most complex challenges. We deliver projects from inception through completion, embracing challenges to empower communities worldwide. Learn more at www.dar.com.
Our Vision and Values:
We aspire to be the chosen home of those with a gift for crafting solutions that empower people and an unwavering passion for learning and innovation. Our core values shape our culture and guide our decision-making. We are committed to:
- Excellence
- Responsibility
- Empowerment
- Connectivity
- Courage
Job Purpose:
The MLOps Engineer will streamline and automate the deployment, monitoring, and scaling of machine learning models in production. This role bridges the gap between data science and operations to ensure reliable, efficient, and continuous model delivery within the AEC technology ecosystem.
Responsibilities:
The role includes, but is not limited to:
- Maintain ML pipelines, including data and model versioning, for re-training, testing, and deployment.
- Implement automated CI/CD workflows for machine learning models and data pipelines.
- Monitor model performance using KPIs and metrics, ensuring system reliability in production.
- Manage infrastructure, version control, and model reproducibility using cloud, on-prem, and containerization tools.
- Integrate MLOps modules into the existing AI platform to enhance operational efficiency.
- Optimize cost, performance, and scalability of ML environments.
- Collaborate with data scientists, AI engineers, computational designers, and design engineers to embed advanced digital solutions into enterprise workflows.
- Stay current with MLOps trends and recommend improvements to existing systems and processes.
- Support project planning, documentation, and presentations.
- Mentor colleagues and contribute to knowledge sharing within the team.
Values Alignment
- Demonstrates analytical thinking, independence, professionalism, transparency, and accountability.
- Communicates effectively and fosters collaboration across cross-functional teams.
- Upholds quality outcomes while embodying the organization's core values in all actions.
Requirements:
- Bachelor's or master's in computer science, Software Engineering, Artificial Intelligence, Data Engineering, or a related field.
- 13 years of professional experience in at least three of the following: ML deployment, automated CI/CD, ML monitoring, machine learning, deep learning, LLMs, NLP, reinforcement learning, or computer vision.
- Strong proficiency in Python, C#/C++, and SQL.
- Experience with cloud platforms (AWS, Azure, or GCP).
- Hands-on experience with ML frameworks (TensorFlow, PyTorch) and MLOps tools (MLflow, Docker, Kubernetes).
- Knowledge of CI/CD systems, data versioning, and monitoring tools.
- Excellent problem-solving, collaboration, software development, and automation skills.
- Familiarity with AEC tools (Revit, Rhino, AutoCAD, Navisworks) is a plus.
Kind Note:
* While we carefully review all applications, only candidates meeting the specified requirements will be contacted for further consideration. We appreciate your understanding and thank all applicants for their interest.
