Senior ML Engineer - Remote AI Solutions Lead

Hire Feed

Napoli

Remoto

EUR 106.000 - 158.000

Tempo pieno

2 giorni fa
Candidati tra i primi
Generatore di candidature

Trasforma questo ruolo in un colloquio — un curriculum e una lettera di presentazione personalizzati in base a ciò che cerca questo datore di lavoro.

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Descrizione del lavoro

Hire Feed is seeking a Senior Machine Learning Engineer to design, develop, and deploy ML models in a remote, full-time role. You will collaborate with cross-functional teams to integrate AI solutions into production systems.

The ideal candidate has deep experience with Python and ML frameworks, data preprocessing, and cloud deployment, with a focus on scalable pipelines, performance optimization, and MLOps practices.

Competenze

  • Proficiency in Python and ML frameworks such as TensorFlow or PyTorch.
  • Experience with data preprocessing, feature engineering, and model evaluation.
  • Knowledge of cloud platforms for model deployment (AWS, GCP, or Azure).
  • Familiarity with MLOps practices, including CI/CD for ML workflows.
  • Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.

Mansioni

  • Design and implement machine learning models using Python, TensorFlow, and PyTorch.
  • Develop scalable data pipelines to support model training and inference.
  • Optimize models for performance, accuracy, and latency in production environments.
  • Collaborate with software engineers to deploy models as APIs or microservices.
  • Monitor model performance and retrain systems as needed to maintain accuracy.

Conoscenze

Python
TensorFlow
PyTorch
Data preprocessing
Feature engineering
Model evaluation
Cloud platforms (AWS/GCP/Azure)
MLOps / CI-CD

Descrizione del lavoro

Hire Feed is seeking a Senior Machine Learning Engineer to design, develop, and deploy ML models in a remote, full-time role. You will collaborate with cross-functional teams to integrate AI solutions into production systems.

The ideal candidate has deep experience with Python and ML frameworks, data preprocessing, and cloud deployment, with a focus on scalable pipelines, performance optimization, and MLOps practices.

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