Machine Learning Operations (ML Ops) Engineer – On Premise
Job ID:
621649
02 Apr 2026
Machine Learning Operations , Python
Jobseekers from any country
Key Responsibilities
Manage end-to-end ML lifecycle including deployment, monitoring, and scaling of models
Implement and maintain GPU-based machine learning infrastructure
Develop and manage containerized environments using Docker
Orchestrate ML workloads using Kubernetes in on-premise environments
Optimize performance and resource utilization for ML pipelines
Collaborate with data science teams to productionize machine learning models
Monitor system performance and ensure reliability and security compliance
Integrate and manage vector databases such as Pinecone, FAISS, or Milvus
Maintain documentation and best practices for ML operations and infrastructure
Requirements & Qualifications
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field
Strong experience in MLOps, machine learning infrastructure, or DevOps for AI systems
Hands-on experience with GPU-based deployments and high-performance computing
Proficiency in Docker and Kubernetes for containerization and orchestration
Experience with ML lifecycle management and model deployment pipelines
Familiarity with vector databases such as Pinecone, FAISS, or Milvus is a plus
Knowledge of cloud and on-premise hybrid environments is advantageous
Strong problem-solving, analytical, and communication skills
Experience working in regulated environments such as banking or finance is preferred
SAR 18,000 – 30,000 per month (based on experience level and MLOps roles in Saudi Arabia banking sector)
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