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Machine Learning Engineer (Remote)

Quik Hire Staffing
Abu Dhabi, UAE
Contract
Entry
Onsite
$20 to $90 per hour
Discovered 1 weeks ago
PythonMachine learningTensorFlowPyTorchCloud platformsAWS
Free

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Role Overview

The employer is hiring a Machine Learning Engineer to work on a contract basis.

The role involves designing, developing, and deploying machine learning models to solve complex business challenges.

The engineer will collaborate with cross-functional teams to integrate AI solutions into existing systems and optimize model performance.

Compensation

  • The payout is $20 to $90 per hour.

Workplace and Job Type

  • The position is remote and can be performed from anywhere.
  • The job type is contract.

Key Responsibilities

  • Design and implement machine learning models using Python, TensorFlow, or PyTorch.
  • Collaborate with data scientists and software engineers to deploy models into production environments.
  • Optimize and fine-tune models for scalability, accuracy, and efficiency.
  • Develop and maintain pipelines for data preprocessing, feature engineering, and model training.
  • Conduct experiments to evaluate model performance and improve solutions based on business needs.

Required Skills and Qualifications

  • Proficiency in Python and experience with TensorFlow or PyTorch.
  • Strong knowledge of data structures, algorithms, and statistical modeling techniques.
  • Experience with AWS, Google Cloud, or Azure for model deployment and scaling.
  • Knowledge of SQL and databases for data extraction and preprocessing.
  • Familiarity with Git and collaborative development workflows.
  • Understanding of MLOps practices for monitoring, logging, and continuous integration.
  • Experience with hyperparameter tuning and model optimization techniques.
  • Ability to work independently and manage multiple tasks in a fast-paced environment.

Opportunity Context

The role supports AI-driven solutions intended to improve operational efficiency and customer experiences.

The engineer will solve high-impact problems using modern tools and methodologies.

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