ML Ops Engineer Freelance starting asap

  • Type Régie
  • BUDGET Tarif selon profil
  • Durée (mois) 6
  • Pays France
  • Remote NON
  • Offres0
  • Moyenne Tarif selon profil
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Publiée le 27 août 2024

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Description de la mission

As an ML Ops Engineer, you will be responsible for the deployment, monitoring, and maintenance of machine learning (ML) models in a production environment. You will work closely with data scientists, software engineers, and other stakeholders to implement scalable and efficient ML operational solutions, with a particular focus on leveraging Google Cloud Platform (GCP) services. Your responsibilities include:
Model Deployment and Monitoring
Deploy machine learning models in batch and real-time environments on GCP.
Implement robust monitoring and alerting for ML models in production.
Develop model retraining strategies and manage workflow orchestration using Vertex AI.
Track experiments and manage model registry and versioning using tools like Vertex AI or MLflow.
System Design and Integration
Design and implement data ingestion and preprocessing pipelines using GCP services.
Implement ETL/ELT processes for data management.
Handle big data using tools like Pyspark and Polars.
Utilize GCP services such as Pub/Sub, Dataproc, and Dataflow for data streaming.
Work with both SQL and NoSQL databases for data storage and retrieval.

Compétences Techniques Requises

MonitoringPySparkSystem design

Compétences Fonctionnelles Requises

Design

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