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AI & Data Engineer (m/f/x)
Résumé du poste
A product development firm in Kuala Lumpur is looking for an AI & Data Engineer to design, implement, and optimize data pipelines and machine learning solutions. The ideal candidate will have over 4 years of experience in data engineering and strong skills in Python, cloud platforms, and MLOps tools. This role offers flexible work hours and exciting projects within a collaborative international team.
Prestations
Qualifications
- 4+ years of experience in data engineering, machine learning or AI development.
- Strong proficiency in Python and relevant libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).
- Experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes).
- Solid understanding of data architecture, cloud platforms (AWS, Azure), and CI/CD pipelines.
- Familiarity with SQL, NoSQL, and data engineering tools (e.g., Spark, Hadoop, Talend, Informatica, Snowflake, BigQuery).
- A positive attitude, a collaborative spirit, and excellent communication skills.
Responsabilités
- Develop and maintain scalable data pipelines and ETL processes.
- Build and deploy machine learning models using modern frameworks and tools.
- Design and implement MLOps workflows for model training, validation, deployment, and monitoring.
- Collaborate with data scientists, software engineers, and product teams to deliver AI-powered solutions.
- Ensure data quality, security, and compliance across systems.
- Optimize performance of data and ML systems in cloud environments.
- Stay up-to-date with latest trends in AI, data engineering, and MLOps.
Connaissances
Outils
About the role
We’re looking for a skilled and forward-thinking AI & Data Engineer to join our international, multi-country team. In this role, you’ll design, build, and optimize data pipelines and machine learning infrastructure that power intelligent applications and data-driven decisions. You’ll work at the intersection of Data Engineering, Machine Learning, and MLOps, helping us scale AI solutions from experimentation to production.
Develop and maintain scalable data pipelines and ETL processes.
Build and deploy machine learning models using modern frameworks and tools.
Design and implement MLOps workflows for model training, validation, deployment, and monitoring.
Collaborate with data scientists, software engineers and product teams to deliver AI-powered solutions.
Ensure data quality, security, and compliance across systems.
Optimize performance of data and ML systems in cloud environments.
Stay up-to-date with the latest trends in AI, data engineering, and MLOps.
4+ years of experience in data engineering, machine learning or AI development.
Strong proficiency in Python and relevant libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).
Experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes).
Solid understanding of data architecture, cloud platforms (AWS, Azure), and CI/CD pipelines.
Familiarity with SQL, NoSQL, and data engineering tools (e.g., Spark, Hadoop, Talend, Informatica, Snowflake, BigQuery).
A positive attitude, a collaborative spirit, and excellent communication skills.
- Exciting projects
- Flexible working hours
- ARRK Engineering Academy
- Employee events
- Creative scope
- Pleasant working atmosphere
Iliana Morales Reyes
+ 49 (0)89 / 31857-0
ARRK Engineering is part of the international ARRK group of companies and specializes in product development. Within the ARRK group of companies we implement product developments from virtual development to prototypes and small series production.
For reasons of simplification, only the masculine form is used in this job advertisement. However, persons of any gender and any orientation are always meant equally. Our job offer is equally directed at severely disabled persons and persons of equal status.
* Le salaire de référence se base sur les salaires cibles des leaders du marché dans leurs secteurs correspondants. Il vise à servir de guide pour aider les membres Premium à évaluer les postes vacants et contribuer aux négociations salariales. Le salaire de référence n’est pas fourni directement par l’entreprise et peut pourrait être beaucoup plus élevé ou plus bas.