Senior Machine Learning Engineer

September 25, 2024

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SageSure

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SageSure is a leading provider of property insurance products to homeowners and small businesses in coastal states. As an innovation-focused company, SageSure utilizes advanced technology to offer tailored insurance solutions, ensuring comprehensive coverage and risk management.

Innovative Property Insurance Products • MGU

501 - 1000 employees

👥 B2C

💸 Finance

📋 Description

• Play a crucial role in optimizing orchestration processes and ensuring fast and efficient model deployment and delivery. • Work closely with Software Engineers and Data scientists to streamline machine learning pipelines and implement best practices for managing and deploying ML models. • 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. • Collaborate with cross-functional teams to identify bottlenecks and implement solutions to improve workflow efficiency.

🎯 Requirements

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field. • 5-7 years of experience as an MLOps Engineer or similar role, with a proven track record of optimizing machine learning pipelines and infrastructure. • 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. • 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.

🏖️ Benefits

• Generous health benefits • Tuition reimbursement • Wellness allowance • Paid volunteer time off • 401K matching plan