Design, implement, and manage robust MLOps pipelines for deploying, monitoring, and maintaining machine learning models in production environments. Collaborate with cross-functional teams, including data scientists, software engineers, and DevOps, to...
תיאור:You will:
- Design, implement, and manage robust MLOps pipelines for deploying, monitoring, and maintaining machine learning models in production environments.
- Collaborate with cross-functional teams, including data scientists, software engineers, and DevOps, to ensure seamless integration of ML models into existing systems and processes.
- Continuously improve the CI/CD processes to automate model training, evaluation, and deployment.
- Implement and maintain monitoring solutions to track model performance, data quality, and system reliability.
- Troubleshoot and resolve issues related to machine learning infrastructure and pipelines.
- Keep abreast of the latest trends and best practices in MLOps and contribute to the evolution of our ML deployment strategies.
Essential Requirements
- Bachelor's degree or higher in Computer Science, Engineering, or a related field. Advanced degrees are a plus. Written and spoken English.
- Strong experience in MLOps or a related field.
- Proficiency in deploying and managing machine learning models using tools like Kubernetes, Docker, and orchestration platforms (e.g., Kubernetes, Apache Airflow).
- Strong programming skills in languages like Python, and experience with version control systems (e.g., Git).
- Solid understanding of containerization, virtualization, and infrastructure as code (IaC) principles. Experience with monitoring and logging tools (e.g., Prometheus, ELK stack)
Desirable Requirements
- Experience with ML frameworks (e.g., TensorFlow, PyTorch) and data processing libraries (e.g., pandas, NumPy). Knowledge of security best practices in ML deployments.
- Previous experience with CI/CD pipelines and automated testing for ML models. Familiarity with ML model deployment orchestration platforms like MLflow or Kubeflow.
08 September 2025