Remote ML Engineer: Scalable Pipelines, AWS & Kubernetes

Crossing Hurdles

La Réunion

Sur place

EUR 60 000 - 90 000

Plein temps

Il y a 9 jours

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Résumé du poste

Crossing Hurdles in France seeks a machine learning engineer to design, build, and optimize production ML models, and automate end-to-end pipelines with CI/CD practices.

You will leverage AWS for scalable infrastructure and deploy containerized workloads with Kubernetes, collaborating with data scientists and engineers to translate business problems into ML solutions.

Strong programming in Python or Java, and experience with CI/CD, cloud services, and Kubernetes are essential.

Qualifications

  • Proven expertise in machine learning algorithms, model development and deployment.
  • Strong programming skills in Python or Java, with experience in large-scale software projects.
  • Hands-on experience with CI/CD workflows and automation tools.
  • Hands-on expertise with AWS cloud services for ML applications and data pipelines.
  • Advanced knowledge of Kubernetes for orchestrating containerized ML workloads.

Responsabilités

  • Design, build, and optimize robust machine learning models for production environments.
  • Implement and automate end-to-end ML pipelines using CI/CD best practices.
  • Leverage AWS services for scalable AI infrastructure and model deployment.
  • Orchestrate containerized workloads using Kubernetes for high availability and scalability.
  • Collaborate with data scientists, engineers, and researchers to translate business problems into ML solutions.
  • Evaluate, preprocess, and frame real-world data problems for effective ML applications.

Connaissances

Machine learning
Python
Java
CI/CD
AWS
Kubernetes
Data pipelines

Description du poste

Crossing Hurdles in France seeks a machine learning engineer to design, build, and optimize production ML models, and automate end-to-end pipelines with CI/CD practices.

You will leverage AWS for scalable infrastructure and deploy containerized workloads with Kubernetes, collaborating with data scientists and engineers to translate business problems into ML solutions.

Strong programming in Python or Java, and experience with CI/CD, cloud services, and Kubernetes are essential.

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