AI/ML Computational Science Manager

Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Data Engineering · Software Engineering

In short

We are seeking an experienced AI/ML Engineering Manager in Dubai to lead the development and deployment of scalable AI and machine learning solutions. This role involves leveraging cloud AI services, deep learning, and Generative AI across various environments and leading R&D for new algorithms and models.

Responsibilities

Design and develop AI and ML systems using existing cloud AI services and platforms.
Architect and build scalable data pipelines for model training and production, applying DevOps and MLOps best practices.
Customize and apply Deep Learning and Generative AI models to business use cases, including edge devices and HPCs.
Evaluate and justify the quality, performance, and business value of AI solutions to stakeholders.
Lead research and development of new AI and high-performance compute algorithms, models, and simulations.
Work with large-scale datasets and apply data preprocessing techniques.
Implement and maintain efficient data storage and retrieval mechanisms.
Lead, mentor, and develop a team of AI/ML engineers and data scientists.
Partner with clients and business stakeholders to identify AI opportunities and drive delivery.

Requirements

10+ years of experience in AI/ML engineering, data science, or software engineering, including proven experience leading technical teams.
Hands-on experience with at least one major cloud AI platform (e.g., Azure AI / Azure ML, AWS SageMaker / Bedrock, Google Vertex AI).
Strong programming skills in Python and deep learning frameworks such as PyTorch or TensorFlow.
Solid expertise in Deep Learning and Generative AI, including LLMs, fine-tuning, Retrieval-Augmented Generation (RAG), and prompt engineering.
Strong MLOps and DevOps experience: CI/CD, Docker, Kubernetes, MLflow or Kubeflow, and model monitoring in production.
Experience building large-scale data pipelines with tools such as Spark, Databricks, Airflow, or Kafka.
Experience with data storage and retrieval technologies, including SQL/NoSQL databases, data lakes, and vector databases (e.g., FAISS, Milvus, Pinecone).
Experience optimizing and deploying models on edge devices (e.g., ONNX, TensorRT, quantization) and/or HPC environments (e.g., CUDA, distributed training).
Ability to communicate technical solutions and their business value clearly to senior stakeholders.

Desired Qualifications

Master's or PhD in Computer Science, Artificial Intelligence, Data Science, Applied Mathematics, or a related field.
Track record in AI or HPC research, such as publications, patents, or simulation work.
Relevant cloud AI certifications (Azure, AWS, or Google Cloud).
Consulting or client-facing delivery experience.

Benefits

Opportunities to keep skills relevant through certifications, learning, and diverse work experiences.
Consistently recognized as one of the World’s Best Workplaces™.
Work with the promise of technology and human ingenuity.
Drive positive change and deliver value to clients, partners, shareholders, communities, and each other.
Inclusive and diverse environment where everyone feels a sense of belonging and is respected and empowered.
Holistic well-being support, including physical, mental, and financial health.

Skills

PythonPyTorchTensorFlowDockerKubernetesMLflowKubeflowSparkDatabricksAirflowKafkaSQLNoSQLFAISSMilvusPineconeONNXTensorRTCUDA

#AI#Machine Learning#Computational Science#Manager#Python#Deep Learning#Generative AI#Cloud#Edge Computing#HPC

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