Machine Learning Engineer | Remote

Crossing Hurdles; La Réunion; Sur place; EUR 60 000 - 90 000; Plein temps

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

• 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 to ensure high availability and seamless scalability.
• Collaborate with data scientists, engineers, and researchers to translate complex business problems into actionable ML solutions.
• Evaluate, preprocess, and frame real-world data problems for effective machine learning applications.

Requirements

• Have proven expertise in machine learning algorithms, model development, and deployment.
• Possess strong programming skills, ideally in Python or Java, with experience in large-scale software engineering projects.
• Have in-depth experience with CI/CD workflows and automation tools.
• Have hands-on expertise with AWS cloud services for ML applications and data pipelines.
• Have advanced knowledge of Kubernetes for orchestrating containerized ML workloads.