Job description

About Us Quantum HR is a premier human resources consulting firm dedicated to connecting exceptional talent with leading organizations worldwide.
We specialize in providing bespoke recruitment solutions, leveraging deep industry insights and a global network to help companies build high-performing teams by matching them with professionals who truly fit their needs and culture.
About the Role We’re hiring an AI Platform Engineer to support our team in deploying and maintaining a robust AI platform that powers innovative solutions across our organization.
In this role, you will be responsible for managing the deployment and configuration of AI platform components, enabling smooth model serving, and orchestrating services within our existing architecture.
You will play a crucial role in ensuring platform reliability, managing access controls, and coordinating with cross-functional engineering teams to drive the success of AI initiatives.
This is an individual contributor role that offers significant ownership over system design and integration, as you work to evolve and enhance our AI capabilities in a scalable and efficient manner.
Key Responsibilities Model Deployment & Management : Enable efficient model serving and orchestration by ensuring that AI models are deployed smoothly and effectively integrated within the broader solution architecture.
Environment Configuration : Configure and manage various environments to support optimal performance and reliability of AI services.
Integration : Facilitate the integration of AI services into existing software architectures and workflows, ensuring seamless operations between models and other systems.
Platform Reliability : Monitor and enhance platform reliability through effective troubleshooting, access control mechanisms, and environmental management.
Collaboration : Work closely with cross-functional engineering teams, data scientists, and stakeholders during deployment and operational phases to ensure alignment and success of the AI initiatives.
Experience : 4 to 6 years of relevant professional experience in AI platform engineering, MLOps, or equivalent engineering roles supporting production AI systems.
Technical Skills : Proven expertise in deploying machine learning models, configuring environments, service integration, and conducting operational troubleshooting.
Proficiency in programming languages such as Python and familiarity with libraries like TensorFlow or PyTorch is essential.
MLOps Proficiency : Experienced in the use of MLOps tools such as MLflow or Kubeflow for managing the ML lifecycle and orchestrating workflows with tools like Apache Airflow.
Infrastructure Understanding : Solid understanding of containerization technologies (such as Docker and Kubernetes) and cloud platforms (AWS, Google Cloud, or Azure) for deploying AI solutions.
Coordination Skills : Strong ability to coordinate efforts across data, backend, and platform environments, and effectively communicate technical concepts to non-technical stakeholders.
Language Proficiency : Fluent in both Arabic and English, with excellent verbal and written communication skills.
Preferred Qualifications: Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
Familiarity with database management systems, both SQL (e.
g., PostgreSQL, MySQL) and NoSQL (e.
g., MongoDB, Cassandra).
Experience with data governance, access controls, and security protocols.
A proactive problem solver who thrives in a collaborative, fast-paced environment.