Machine Learning Engineer

About The Project

We are developing a fine-tuning automation platform for an AI team, streamlining model adaptation, data collection, and evaluation. The PoC phase focuses on fine-tuning OpenAI’s Whisper model for Arabic transcription, validating performance improvements, and ensuring on-premises deployment feasibility.

Phase: Proof of Concept

Engagement: Short-Term (1.5 months, with potential extension)

Responsibilities

• Model Fine-Tuning;
• Data Collection & Preprocessing;
• Model Evaluation & Benchmarking;
• Deployment & Infrastructure.
  
  

Requirements

• 4+ years of commercial experience;
• Proficiency in Python, PyTorch, and Hugging Face Transformers;
• Good understanding of LoRA/QLoRA fine-tuning techniques (Preferably hands-on expertise);
• Strong background in data preprocessing and augmentation (preferably for speech recognition);
• Ability to work independently within a short PoC timeframe;
• Upper-Intermediate level of English and higher.
  
  

Nice To Have

• Experience in Speech-to-Text (STT) models (preferably Whisper or similar);
• Experience with WER, CER, and BLEU score evaluations;
• Familiarity with Gradio, NeptunAI, and on-premises ML deployments;
• Prior experience in automating fine-tuning pipelines;
• Familiarity with distributed training and optimization techniques.
  
  

Our Benefits

• Professional and career growth promotion;
• Competitive salary;
• Flexible working hours;
• Regular technical training at our office.