Remote Data Science Engineer: Scalable ML & Pipelines

HUMAN-AI-Z Nexus Technology; Dubai; On-site; AED 200,000 - 420,000; Full time

Job summary

HUMAN-AI-Z Nexus Technology is seeking a Data Science engineer to design, build, and deploy ML models and data pipelines in a remote contract role. You will collaborate with cross-functional teams to translate business requirements into scalable AI solutions.

The role involves production-grade model development, data pipeline design, and deployment in cloud environments, with a focus on accuracy, scalability, and cost-efficiency. Remote-first work creates opportunities to impact global projects.

Qualifications

• Proficiency in Python with data science libraries.
• Experience with ML frameworks (TensorFlow, PyTorch).
• Strong background in statistical modeling and ML techniques.
• Familiarity with cloud platforms (AWS, GCP, Azure) and big data tools.
• Experience with SQL and data extraction.
• Write clean, maintainable code with good documentation.
• Understanding of MLOps, deployment and monitoring.
• Experience with Git and version control.

Responsibilities

• Develop and maintain production-grade data science models in Python.
• Design data pipelines for large-scale datasets for training and inference.
• Collaborate with software engineers to integrate models into production systems and APIs.
• Optimize models for performance, scalability, and cloud cost-efficiency.
• Conduct rigorous testing and validation for accuracy and reliability.

Skills

Python

NumPy

Pandas

Scikit-learn

TensorFlow

PyTorch

Cloud platforms

SQL

Git

MLOps

Tools

Spark

Hadoop

Docker

Job description

HUMAN-AI-Z Nexus Technology is seeking a Data Science engineer to design, build, and deploy ML models and data pipelines in a remote contract role. You will collaborate with cross-functional teams to translate business requirements into scalable AI solutions.

The role involves production-grade model development, data pipeline design, and deployment in cloud environments, with a focus on accuracy, scalability, and cost-efficiency. Remote-first work creates opportunities to impact global projects.