Senior Machine Learning Engineer

SageSure Insurance Managers LLC; Jersey City (NJ); Hybrid; USD 150,000 - 190,000; Full time

Job summary

SageSure Insurance Managers LLC is seeking a Senior Machine Learning Engineer to advance data-driven strategies in catastrophe-exposed property insurance. You will design robust ML data pipelines, build prediction workflows, and create APIs to connect models with software components, ensuring secure, scalable production-grade deployments across platforms.

You will collaborate with software engineers and data scientists to optimize orchestration, monitor model performance, and drive

Qualifications

• 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.

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.
• Collaborate with cross-functional teams to identify bottlenecks and implement solutions to improve workflow efficiency.

Job description

Overview:

If you're looking for the stability of a profitable, growing company with the entrepreneurial spirit of a startup, we’re hiring. SageSure, a leader in catastrophe-exposed property insurance, is seeking a Machine Learning Engineer. As a Senior Machine Learning Engineer, you'll play a crucial role in optimizing orchestration processes and ensuring fast and efficient model deployment and delivery. You'll work closely with Software Engineers and Data scientists to streamline machine learning pipelines and implement best practices for managing and deploying ML models.

Overview:

If you're looking for the stability of a profitable, growing company with the entrepreneurial spirit of a startup, we’re hiring. SageSure, a leader in catastrophe-exposed property insurance, is seeking a Machine Learning Engineer. As a Senior Machine Learning Engineer, you'll play a crucial role in optimizing orchestration processes and ensuring fast and efficient model deployment and delivery. You'll work closely with Software Engineers and Data scientists to streamline machine learning pipelines and implement best practices for managing and deploying ML models.

What you’d be doing:

• 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.

We’re looking for someone who has:

• 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.

Data at SageSure

At SageSure, data isn’t just a function—it’s a force for innovation. Our Data organization brings together Data Science, Business Intelligence, and Data Management to power smarter decisions and deliver meaningful impact across the business. From predictive modeling to scalable data ecosystems and actionable insights, we turn complex information into clarity that drives real results.

We’re building a team of curious, collaborative problem-solvers who are passionate about using data to make a difference. Whether you’re advancing machine learning capabilities, strengthening data governance, or uncovering insights that shape strategy, you’ll play a critical role in defining how SageSure uses data to lead the future of insurance.

About SageSure

Named among the Best Places to Work in Insurance by Business Insurance for four years in a row (2020-2023), SageSure is one of the largest managing general underwriters (MGU) focused on catastrophe-exposed property in the US. Since its founding in 2009, SageSure has experienced exceptional growth while generating underwriting profits for carrier partners through hurricanes, wildfires, and hail. Available in 16 states, SageSure offers more than 110 home, flood, and commercial products on behalf of its highly rated carrier partners. Today, SageSure manages more than $3.2 billion of inforce premium and helps protect more than 970,000 policyholders.

We have more than 1,000employees in a distributed workforce environment across 12 offices—Fairfield, CA; Mountain View, CA; Cheshire, CT; Jacksonville, FL; Tallahassee, FL; Tampa, FL; Chicago, IL; Jersey City, NJ; Marlton, NJ; Cincinnati, OH; Houston, TX; Sheboygan, WI—who are tackling the industry’s toughest challenges.

SageSure is a proud Equal Opportunity Employer committed to building a workforce that reflects the spectrum of perspectives, experiences, and abilities of the world we live in. We recognize that our differences make us strong, and we actively seek out diverse candidates through partnerships with organizations, institutions and communities that represent various backgrounds. We champion belonging and inclusion for all identities, including, but not limited to, race, ethnicity, religion, sexual orientation, age, veteran status, ability status, gender, and country of origin, striving to create a culture where all individuals feel valued, respected, and empowered to bring their authentic selves to work.

Our nimble, highly responsive culture nurtures critical thinkers who run toward problems and engineer solutions. We relentlessly pursue better outcomes by investing in the technology, talent, and tools that position us to succeed in demanding markets. Come join our team! Visit sagesure.com/careers to find a position for you.

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