Senior Specialist, Data Science & Artificial Intelligence

Maaden; Riyadh; On-site; SAR 120,000 - 180,000; Full time

Job summary

Maaden in Riyadh is looking for a Machine Learning Engineer to design and implement AI solutions, ensuring technical robustness and performance. Applicants should have a Bachelor’s degree in Data Science or related fields and 4–6 years of relevant experience.

Key duties include developing generative AI models, employing MLOps strategies, and conducting performance evaluations. Strong skills in Python, SQL, and machine learning frameworks are essential.

Qualifications

• 4–6 years in data science, machine learning, or applied AI roles.

Responsibilities

• Design, develop, and deploy machine learning and Generative AI solutions.
• Implement prompt engineering strategies and retrieval-augmented generation (RAG) pipelines.
• Perform feature engineering and model optimization.
• Support deployment of ML and GenAI models using MLOps and LLMOps practices.
• Conduct structured evaluation of LLM outputs.

Skills

Python

SQL

ML frameworks (TensorFlow, PyTorch, Scikit-learn)

Prompt engineering

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

Education

Bachelor’s degree in Data Science, Artificial Intelligence, Computer Science, or a related quantitative field

Job description

Job Description

Design, develop, and deploy machine learning and Generative AI solutions to solve defined business problems, ensuring technical robustness, model performance, and responsible AI implementation.

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 Qualifications, 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
• 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