In this role, you will design, develop, and deploy machine learning and Generative AI solutions aimed at solving defined business challenges. Your focus will be on ensuring the technical robustness of models, optimizing performance, and implementing responsible AI practices.
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Key Accountabilities
- Develop, test, and validate machine learning, deep learning, and Generative AI models (including LLM-based applications).
- Implement prompt engineering strategies and retrieval-augmented generation (RAG) pipelines.
- Perform feature engineering, model tuning, and performance optimization.
- Prepare, cleanse, and transform structured and unstructured datasets.
- Support deployment of ML and GenAI models using MLOps and LLMOps practices.
- Conduct structured evaluation of LLM outputs including hallucination detection and quality scoring.
- Integrate AI solutions via APIs into enterprise systems.
- Document model design, assumptions, risks, and validation results.
- Ensure compliance with data governance, cybersecurity, and ethical AI guidelines.
- Support monitoring, retraining, and lifecycle management of deployed models.
Minimum Qualification, Experience and Competencies
- Minimum Qualification: Bachelor’s degree in Data Science, Artificial Intelligence, Computer Science, or a related quantitative field
- Minimum Experience: 4–6 years in data science, machine learning, or applied AI roles.
Skills
- Python, SQL, ML frameworks (TensorFlow, PyTorch, Scikit-learn)
- Prompt engineering for RAG pipelines & vector databases
- Model fine-tuning and evaluation
- Data preprocessing & feature engineering
- Basic cloud deployment concepts
- MLOps / LLMOps fundamentals
- Analytical problem-solving
- Results Orientation
- Collaboration
- Continuous Improvement
- Accountability
Benefits
- Career Growth
- Competitive Salaries
- Comprehensive Package
- Inclusive Work Environment
- Work-Life Balance
- Employee wellness
Location
Riyadh, Saudi Arabia
