Machine Learning Engineer

Dicetek LLC; Dubai; Presencial; AED 420.000 - 550.000; Jornada completa

Descripción de la vacante

Dicetek LLC invites an experienced ML Engineer to design, build and deploy scalable machine learning solutions in production. You will preprocess data, engineer features, select models, and establish robust validation, monitoring and governance practices.

You will drive experimentation, AB testing, and collaborate with stakeholders to translate findings into business value. Dubai-based role requiring strong Python, ML library, and AWS expertise.

Formación

• 6-7+ years across Data Science or ML roles with production models.
• Experience deploying models to production and maintaining pipelines.
• Knowledge of model governance, validation, and documentation is advantageous.

Responsabilidades

• Develop and deploy ML models to solve complex business problems.
• Data preprocessing and feature engineering to improve model accuracy.
• Evaluate models with appropriate metrics and validate generalization.
• Design experiments and A/B tests to measure production impact.
• Communicate technical findings to technical and business stakeholders.

Conocimientos

Python

machine learning

AWS

SQL

Data preprocessing

Herramientas

scikit-learn

XGBoost

LightGBM

pandas

NumPy

SageMaker

Descripción del empleo

Develop and deploy machine learning models Build train and deploy machine learning models to solve complex business problems ensuring they meet performance and scalability requirements Data preprocessing and feature engineering Transform raw data into formats suitable for machine learning algorithms including data cleaning feature selection and feature engineering to improve model accuracy Model evaluation and validation Evaluate model performance using appropriate metrics validate models to ensure they generalize well and identify areas for improvement Experiment design and A B testing Design and execute experiments to compare different models and approaches including A B testing to measure model impact in production Years of Experience *

Years of Experience

Minimum 6-7 years of relevant experience

Required Skills

• Strong hands‑on Python for machine learning and production‑quality software development.
• Solid knowledge of supervised and unsupervised learning, feature engineering, model selection, cross‑validation and performance metrics.
• Practical experience with common ML libraries such as scikit‑learn, XGBoost, LightGBM, pandas and NumPy; deep learning frameworks where relevant.
• Good SQL skills and experience working with large, complex datasets.
• Experience productionizing models, including packaging, APIs, batch inference, containers and automated pipelines.
• Hands‑on AWS knowledge, preferably including SageMaker, S3, ECR, ECS/EKS or Lambda, Step Functions and CloudWatch.
• Experience with Git‑based development, code reviews, automated testing and CI/CD fundamentals.
• Understanding of model monitoring, data/model drift, explainability, reproducibility and model lifecycle governance.
• Ability to communicate technical findings clearly to both technical and business stakeholders.

Required Experience / Knowledge Areas

• 6-7+ years across Data Science, Machine Learning Engineering or applied ML roles, with evidence of models deployed into production.
• Experience delivering end‑to‑end ML use cases rather than working only on infrastructure or platform administration.
• Experience in banking, financial services or another regulated industry is preferred.
• Understanding of model governance, validation and documentation expectations in controlled environments is advantageous.

Skills

• Python
• machine learning
• AWS