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Machine Learning Engineer

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Onsite

Machine Learning Engineer

Epergne Solutions

Machine Learning Engineer

Skills

Deep LearningDockerFlaskPythonMachine LearningAIAWSKubernetesNLP / Natural Language ProcessingFastAPIAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Dubai - United Arab Emirates

Work mode:

Onsite

Published on:

21 August 2026

What they need


Job Role :-Machine Learning Engineer

Job Location :- Abu Dhabi, UAE

Experience :- 3-7 Years

Role Overview:-

  • Design, develop, and deploy scalable ML/AI solutions for complex business problems.
  • Build production-grade ML systems covering model development, deployment, optimization, and lifecycle management.

Key Responsibilities:-

  • Work with large and complex datasets to develop data-driven solutions.
  • Develop, train, fine-tune, and optimize ML, deep learning, neural network, Agentic AI, SLM/LLM models .
  • Build end-to-end ML pipelines covering data ingestion, transformation, training, validation, and deployment.
  • Develop and optimize real-time and batch inference solutions.
  • Build ML system architectures and integrate models into production applications.
  • Automate model training, testing, deployment, and monitoring using CI/CD and MLOps practices.
  • Develop model-serving APIs using FastAPI/Flask .
  • Collaborate with cross-functional engineering and business teams to deliver end-to-end AI solutions.
  • Deploy and manage ML solutions on AWS/Azure .

Requirements & Skills:-

  • 3?7 years of experience building and deploying production-grade, scalable AI/ML systems.
  • Strong expertise in supervised/unsupervised learning, deep learning, NLP, computer vision, or Generative AI/LLMs .
  • Strong understanding of ML system architecture and model optimization .
  • Experience with Python and modern ML/AI frameworks .
  • Knowledge of Docker, Kubernetes, CI/CD, MLflow/Kubeflow or similar MLOps tools .
  • Experience with model serving, APIs, and production deployment .
  • Hands-on experience deploying ML models on AWS or Azure .
  • Bachelor?s degree in Computer Science, Engineering, or related field.
  • Master?s/PhD in Computer Science or related field is preferred.
  • Banking Exposure is preferred

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