SageSure is seeking a Machine Learning Engineer to optimize orchestration processes and ensure fast and efficient model deployment and delivery, playing a crucial role in the company's catastrophe-exposed property insurance business.
Requirements
- Proficiency in cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
- Experience with orchestration tools and frameworks such as Airflow, Kubeflow, or MLflow.
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
- Experience in deploying machine learning models in production environments and managing model lifecycle.
- Experience as an MLOps Engineer or similar role, with a proven track record of optimizing machine learning pipelines and infrastructure.
- 5-7 years of experience in a related technical field.
- Proficiency in programming languages such as Python
Responsibilities
- Design and implement robust, scalable, and efficient data pipelines for training machine learning models.
- Develop prediction pipelines to ensure seamless integration of trained models into production environments.
- Create APIs and microservices to facilitate communication between machine learning models and other software modules.
- Design, build, and manage model deployment strategies to ensure reliability, scalability, and security in production environments.
- Implement monitoring and logging solutions to track model performance, data quality, and system health in real-time.
- Optimize orchestration processes to ensure efficient deployment and management of ML models.
- Implement cost-saving strategies to minimize infrastructure expenses while maximizing performance.
Other
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field.
- Excellent problem-solving skills and ability to work independently as well as part of a team.
- Strong communication skills and ability to collaborate effectively with cross-functional teams.
- Ability to work in a remote or in-office setting across nine offices.
- Must be an Equal Opportunity Employer committed to building a workforce that reflects the spectrum of perspectives, experiences, and abilities of the world we live in.
