TAT IT Technolgies
Machine Learning Engineer
TAT IT TechnolgiesQatar2 days ago
ContractEngineering, Information Technology
We have an urgent requirement for Machine Learning Engineer for our client based in Qatar

Develop and implement machine learning models and algorithms to derive insights, predictions, and recommendations from Labour-related data.---Must

 Strong proficiency in programming languages such as Python, R, or Java, with expertise in machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch)---Must

deep learning algorithms, neural networks, and convolutional/recurrent architectures.---Must

 integrate machine learning models into the LMIS infrastructure, including data pipelines and real-time prediction systems.--Must

Background

Client is seeking a skilled and experienced Machine Learning Engineer to contribute to the development and implementation of a Labour Market Information System (LMIS). The LMIS aims to leverage machine learning algorithms and techniques to automate processes, make predictions, and generate actionable insights. The selected Machine Learning Engineer will play a key role in designing, developing, and deploying machine learning models within the LMIS.

Objectives

The main objectives of the Machine Learning Engineer are as follows:

  • Develop and implement machine learning models and algorithms to derive insights, predictions, and recommendations from Labour-related data.
  • Collaborate with the Data Engineering team to ensure the availability, quality, and preprocessing of data for training and validation purposes.
  • Optimize and fine-tune machine learning models to improve accuracy, performance, and efficiency.
  • Deploy machine learning models within the LMIS infrastructure to enable real-time predictions and analysis.
  • Continuously monitor and evaluate model performance, incorporating feedback and iterative improvements.
  • Stay updated with the latest advancements in machine learning, deep learning, and AI to propose innovative solutions and enhance the LMIS.

Responsibilities

The Machine Learning Engineer will be responsible for the following tasks:

  • Collaborate with stakeholders to understand business requirements and identify opportunities for applying machine learning techniques.
  • Perform data preprocessing, feature engineering, and data augmentation to prepare the data for machine learning model development.
  • Develop, implement, and validate machine learning models, including supervised and unsupervised learning algorithms, regression models, and classification models.
  • Optimize models for scalability, performance, and interpretability while ensuring compliance with data privacy and security standards
  • Collaborate with the Data Engineering team to integrate machine learning models into the LMIS infrastructure, including data pipelines and real-time prediction systems.
  • Conduct regular evaluations and model performance monitoring, making necessary adjustments and retraining as needed.
  • Implement version control and documentation processes to maintain model versions and track changes.
  • Collaborate with stakeholders to interpret and present model outputs, insights, and recommendations in a meaningful and actionable manner.
  • Ensure compliance with ethical considerations and legal requirements in the use of machine learning algorithms and data.

Qualifications And Skills

The ideal candidate should possess the following qualifications and skills:

  • Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
  • Proven experience (at least 3 years) in machine learning model development, implementation, and deployment.
  • Strong proficiency in programming languages such as Python, R, or Java, with expertise in machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
  • Experience with data preprocessing, feature engineering, and data augmentation techniques.
  • Understanding of various machine learning algorithms, including supervised and unsupervised learning, regression, and classification.
  • Familiarity with deep learning algorithms, neural networks, and convolutional/recurrent architectures.
  • Knowledge of model evaluation metrics, cross-validation techniques, and hyperparameter tuning.
  • Experience with model deployment and integration in production environments using frameworks like Flask or Docker.
  • Familiarity with cloud platforms and services for scalable model deployment (e.g., AWS, Azure, Google Cloud).
  • Strong problem-solving skills and ability to translate business requirements into machine learning solutions.
  • Excellent communication and collaboration skills to work effectively with stakeholders and contribute to a multidisciplinary team

Deliverables

The Machine Learning Engineer will be responsible for delivering the following key outputs:

  • Developed and validated machine learning models for Labour-related insights, predictions,

and recommendations.

  • Integrated machine learning models into the LMIS infrastructure for real-time predictions.
  • Regular model evaluations and performance monitoring reports.
  • Documentation of machine learning processes, model versions, and deployment procedures

Skills: machine learning,algorithms,learning

Key Skills

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