Senior Machine Learning Engineer

Central Agency Insurance - Dublin, OH

Full-time - Mid Level

Hybrid - Dublin, OH

Insurance Carriers and Related Activities

About the position

The Sr. Machine Learning Engineer at Central's Data Science Center of Excellence will focus on developing and deploying AI/ML solutions to support business stakeholders. This role involves creating innovative machine learning workflows and pipelines, ensuring data quality, and collaborating with product teams to integrate machine learning features into applications. The position offers opportunities for growth and innovation in a hybrid work environment.

Responsibilities

• Understand business objectives and develop solutions that achieve them.
• Present complex analyses clearly and concisely.
• Build collaborative relationships with peers and multi-functional partners.
• Provide live on-call support and own production issues from root cause analysis to resolution.
• Develop ML workflows and end-to-end pipelines for data preparation, training, deployment, and monitoring.
• Drive code reviews to ensure quality and adherence to coding standards.
• Collaborate closely with product teams to lead API development and maintain ML infrastructure.
• Conduct reasonably complex statistical analysis, including predictive and prescriptive modeling.
• Create solutions for business problems that can be integrated into internal systems or software.
• Ensure data quality, security, and availability for data, notebooks, models, and applications.
• Consult with data engineers in the development of data pipelines and tools.
• Provide technical and programmatic support through the entire project life cycle.
• Build production-grade solutions to scale and serve machine learning models.
• Write and edit documentation and technical requirements.
• Provide guidance and mentorship to junior engineers.

Requirements

• Master's degree in a technology-related field such as computer science, engineering, or applied statistics with 2 years of experience in machine learning, or a Bachelor's degree with 4 years of experience, or 6 years of experience in machine learning.
• Proven experience with continuous integration & delivery (CI/CD) practices and tools (Git, Jenkins, uDeploy).
• Proven experience with building container-based systems such as Docker.
• Proven experience with relational and dimensional data modeling techniques.
• Proven experience or strong interest in machine learning models and concepts: regression, random forest, boosting, NLP, and deep learning.
• Proven experience or strong interest in developing and deploying complex and scalable software systems in the analytics space.
• Experience with Azure Data Lake or other cloud data warehousing solutions.
• Exposure to orchestration and scheduling tools (Control-M).
• Proven experience with triaging, troubleshooting, and fixing issues in Production environments.
• Excellent communication skills including written, verbal, and technology diagrams.
• Understanding of the model development lifecycle and exposure to DevOps/MLOps/LLMOps/ModelOps.
• Capable of working independently.
• Experience with enterprise Cloud ML Services (i.e., Sagemaker, AzureML, Vertex AI), and open source AI/ML frameworks.

Nice-to-haves

• Azure certification or AWS certification.