Data / AI Trainers

Excelsior; Riyadh; On-site; SAR 48,000 - 120,000; Full time

Job summary

A technology training firm in Riyadh is seeking AI Trainers for various data-related roles. Candidates must be fluent in Arabic and will be contracted for one year on an hourly basis. Responsibilities include training AI models, documenting processes, and collaborating with teams. Ideal for individuals with experience in AI and data training.

Qualifications

• Must be ARABIC Speakers.
• Experience training AI models and related technologies is required.

Responsibilities

• Train AI models using available datasets and adjust parameters.
• Analyze AI model performance and identify improvement areas.
• Document the training process for transparency and reproducibility.
• Collaborate with data scientists and engineers.
• Stay updated with advancements in AI and machine learning.

Skills

ARABIC Speakers

Job description

Data / AI Trainers

Job Description and Requirements

Description :

Must be ARABIC Speakers

Location- Riyadh ,KSA

The Trainer should be based in Riyadh

The contract is for a period of one year and the trainers will be paid on an hourly basis

They have compulsory 4 hrs training daily and the course content , modules and materials will be provided by the client

• DATA SCIENTIST TRAINER
• AI ENGG TRAINER
• DATA ANALYST TRAINER
• DATA ENGG TRAINER
• CLOUD DATA ENGG TRAINER

As an AI Trainer, your job description typically involves training and refining artificial intelligence models.

• Training and Validation : Training AI models using available datasets and adjusting the model parameters to optimize performance. Evaluating and validating the model's accuracy and effectiveness using appropriate metrics and techniques.
• Model Improvement : Analyzing the performance of AI models and identifying areas for improvement. This may involve fine-tuning the models, adjusting hyperparameters, or incorporating new techniques to enhance accuracy and efficiency.
• Documentation : Documenting the training process, including datasets used, model configurations, and performance metrics. This documentation helps ensure transparency, reproducibility, and knowledge sharing within the team.
• Collaboration and Communication : Collaborating with cross-functional teams, including data scientists, engineers, and domain experts. Communicating effectively to understand project requirements, provide updates on progress, and address any challenges or issues.
• Stay Updated : Keeping up with the latest research, advancements, and best practices in the field of artificial intelligence and machine learning. Continuously learning and incorporating new techniques and approaches into your training processes.