ML Platform Engineer - Generative AI & Machine Learning Infrastructure

• Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models
• Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes
• Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate
• Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference
• Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability
• Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals
• Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components
• Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows

• Bachelor's degree in Computer Science, Engineering, or related field (Master's preferred)
• Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles
• Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain
• Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm)
• Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis
• Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems
• Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies

• Opportunity to work on advanced ML and AI projects impacting millions of users in the Middle East
• Competitive salary and benefits package
• A collaborative, innovation-driven environment with cutting-edge tools and technologies
• Career development in one of the fastest-growing tech ecosystems in the region

• Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models
• Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes
• Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate
• Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference
• Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability
• Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals
• Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components
• Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows

• Bachelor's degree in Computer Science, Engineering, or related field (Master's preferred)
• Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles
• Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain
• Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm)
• Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis
• Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems
• Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies

• Opportunity to work on advanced ML and AI projects impacting millions of users in the Middle East
• Competitive salary and benefits package
• A collaborative, innovation-driven environment with cutting-edge tools and technologies
• Career development in one of the fastest-growing tech ecosystems in the region

Careers in Gulf