Production ML Engineer — AWS Deployments

Halian

Dubai

Sur place

AED 260 000 - 520 000

Plein temps

Il y a 6 jours
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Résumé du poste

Halian in Dubai seeks an experienced Data Scientist to develop predictive and optimization models for client projects. You will design, implement, and productionize ML solutions while collaborating with cross-functional teams to ensure outcomes align with business goals.

The role requires 4+ years in data science with strong Python/SQL and hands-on ML experience, including Scikit-learn, PyTorch, or TensorFlow; GenAI/NLP experience is a plus.

Qualifications

  • Bachelor's degree in CS, Data Science, Mathematics, or related field.
  • 4+ years of experience in Data Science, ML, or Analytics.
  • Strong Python, SQL, and ML experience (Scikit-learn, PyTorch, TensorFlow).
  • Hands-on experience with feature engineering, model tuning, and evaluation.
  • Experience deploying ML solutions on AWS.

Responsabilités

  • Develop predictive and optimisation models using ML and statistics.
  • Build, deploy, and monitor production models on AWS (SageMaker, Lambda, ECS).
  • Design model evaluation frameworks and support A/B testing initiatives.
  • Partner with engineering to ensure scalable, reliable, and high-performing deployments.
  • Monitor model performance, data quality, and drift to drive continuous improvement.

Connaissances

Python
SQL
Machine Learning
Communication

Formation

Bachelor's degree in Computer Science / Data Science / Mathematics

Outils

AWS SageMaker
AWS Lambda
AWS ECS
Scikit-learn
PyTorch
TensorFlow

Description du poste

Halian in Dubai seeks an experienced Data Scientist to develop predictive and optimization models for client projects. You will design, implement, and productionize ML solutions while collaborating with cross-functional teams to ensure outcomes align with business goals.

The role requires 4+ years in data science with strong Python/SQL and hands-on ML experience, including Scikit-learn, PyTorch, or TensorFlow; GenAI/NLP experience is a plus.

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