Senior Machine Learning Engineer at SageSure

Jersey City, New Jersey, United States -

Full Time

Start Date

Immediate

Expiry Date

16 Feb, 26

Salary

0.0

Posted On

18 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Pipelines, APIs, Microservices, Model Deployment, Monitoring, Logging, Cloud Computing, Containerization, Orchestration Tools, Machine Learning Frameworks, Problem-Solving, Communication, Collaboration

Industry

Insurance

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. 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 markets 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 50 competitively priced home, flood, earthquake, and commercial products on behalf of its highly rated carrier partners. Today, SageSure manages more than $1.9 billion of inforce premium and helps protect 640,000 policyholders. SageSure has more than 1000 employees working remotely or in-office across nine offices: Cheshire, Connecticut; Chicago, Illinois; Cincinnati, Ohio; Houston, Texas; Jersey City, New Jersey; Mountain View, California; Marlton, New Jersey; Tallahassee, Florida; and Seattle, Washington. SageSure offers generous health benefits and perks, including tuition reimbursement, wellness allowance, paid volunteer time off, a matching 401K plan, and more. 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.

Responsibilities

As a Senior Machine Learning Engineer, you'll design and implement robust data pipelines for training machine learning models and develop prediction pipelines for production environments. You'll also optimize orchestration processes and collaborate with cross-functional teams to improve workflow efficiency.