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AI developer

MASTER-WORKSالرياض, KSA1 months agoMid-Senior
Mid-Seniorfulltime

Skills

AWSMachine LearningPower BI

About This Role

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** **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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