Senior MLOps Engineer Salla

Responsibilities:

• Design, build, and maintain scalable MLOps pipelines that foster collaboration between data scientists and engineering teams.
• Implement and manage workflows for model training, validation, deployment, and monitoring.
• Utilize cloud-based platforms (AWS, GCP, or Azure) to provision and manage machine learning resources.
• Develop tools and frameworks that assist in continuous integration and deployment of machine learning models.
• Collaborate with data scientists to understand model requirements and assist in feature engineering and selection.
• Monitor model performance in production, identify issues, and provide recommendations for model optimization.
• Establish best practices for versioning, testing, and documenting machine learning models.
• Stay updated with the latest developments in MLOps tools and methodologies.
• Strong communication skills to relay technical concepts to non-technical stakeholders.
• Excellent problem-solving skills and a proactive approach to addressing challenges.

Skills:

• Strong proficiency in programming languages such as Python and familiarity with machine learning frameworks (TensorFlow, PyTorch, etc.).
• Experience with cloud-based platforms like AWS, GCP, or Azure and their machine learning services.
• Hands-on experience with CI/CD processes specific to machine learning applications.
• Professional Experience tools such as Docker and Kubernetes.
• Strong understanding of database technologies (SQL and NoSQL) and data pipeline tools.
• Experience with monitoring tools and practices for ML models in production.
• Ability to work collaboratively in a cross-functional team environment.