Remote AI/ML Engineer — Build Enterprise AI Solutions

Quik Hire Staffing

Terni

Remoto

EUR 104.000 - 156.000

Tempo pieno

3 giorni fa
Candidati tra i primi
Generatore di candidature

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Descrizione del lavoro

Quik Hire Staffing is seeking an AI/ML Engineer (Remote) to design, develop, and deploy machine learning models for enterprise-scale problems. You will work on full-time basis, collaborating with cross-functional teams to integrate AI solutions into production systems.

You should be proficient in Python with TensorFlow or PyTorch, skilled in data preprocessing, feature engineering, and model evaluation, and familiar with cloud deployment and ML lifecycle tools.

Competenze

  • Proficiency in Python with ML libraries such as TensorFlow or PyTorch.
  • Experience with data preprocessing, feature engineering, and model evaluation.
  • Knowledge of cloud platforms (AWS, GCP, or Azure) for deployment and scaling.
  • Familiarity with MLOps practices, including CI/CD pipelines for ML.
  • Strong problem-solving skills and translating business requirements into technical solutions.

Mansioni

  • Design, develop, and optimize machine learning models using Python and relevant frameworks.
  • Preprocess, clean, and transform large datasets for model training.
  • Deploy and monitor machine learning models in production environments.
  • Collaborate with software engineers to integrate AI solutions into existing infrastructure.
  • Conduct performance benchmarking and model validation to ensure accuracy and efficiency.

Conoscenze

Python
TensorFlow/PyTorch
Data preprocessing
Cloud platforms
MLOps CI/CD
Problem solving

Descrizione del lavoro

Quik Hire Staffing is seeking an AI/ML Engineer (Remote) to design, develop, and deploy machine learning models for enterprise-scale problems. You will work on full-time basis, collaborating with cross-functional teams to integrate AI solutions into production systems.

You should be proficient in Python with TensorFlow or PyTorch, skilled in data preprocessing, feature engineering, and model evaluation, and familiar with cloud deployment and ML lifecycle tools.

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