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AI developer

Master Works
Riyadh, KSA
Fulltime
Mid-Senior
3 months ago
AWSMachine LearningPower BIScalaSQL
Free

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AWSMachine LearningPower BI
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Job Description

The charge of creating and developing intelligent solutions using Artificial Intelligence technologies with a focus on generative AI and data science.

The role entails converting data into useful insights and developing AI powered applications that improve decision making and enhance operational efficiency.

Tools & Technologies

Dataiku, Sql server, Power bi, and aws bedrock

Key Responsibilities

  • Design, develop, train, and optimize machine learning models for real applications or use cases
  • Translate business and product requirements into scalable ML/AI solutions
  • Implement feature engineering, model selection, tuning, and evaluation techniques
  • Develop, and deploy ML models into production environments with high availability and performance
  • Build and maintain ML pipelines (training, validation, deployment, monitoring)
  • Monitor model performance, data drift, and model decay; retrain models as needed
  • Ensure models meet reliability, scalability, and security standards
  • Work closely with Data Scientists, Product Managers, and Software Engineers
  • Collaborate with data engineering teams to ensure high-quality, reliable data pipelines
  • Participate in design and code reviews, ensuring engineering best practices
  • Optimize models for latency, throughput, and cost
  • Implement experimentation frameworks (A/B testing, offline evaluation)
  • Apply responsible AI principles, including fairness, explainability, and governance where required

Requirements & Qualifications

  • :
  • +4 years of hands-on experience in Machine Learning or applied AI roles
  • Strong programming skills in Python (and/or Java, Scala)
  • Solid understanding of ML algorithms (supervised, unsupervised, deep learning)
  • Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn
  • Experience deploying models using Docker, Kubernetes, or cloud ML services
  • Strong knowledge of data structures, algorithms, and software engineering principles
  • Experience working in agile, cross-functional teams
  • Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services
  • Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML)
  • Experience with big data technologies (Spark, Kafka, Databricks)
  • Background in NLP, Computer Vision, or Generative AI
  • Strong problem-solving and analytical thinking
  • Production-first mindset
  • Data-driven decision making
  • High Collaboration and communication skills

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