FBS Sr. MLOps Engineer

FBS - Farmer Business Services is part of Farmers operations with the purpose of building a global approach to identifying, recruiting, hiring, and retaining top talent. By combining international reach with US expertise we build diverse and high-performing teams that are equipped to thrive in today's competitive marketplace. Since we don't have a local legal entity, we partnered with Capgemini, which acts as the Employer of Record. Capgemini is responsible for managing local payroll and benefits.

We believe that the foundation of every successful business lies in having the right people with the right skills. That is where we come in—helping Farmers build a winning team that delivers consistent and sustainable results.

• A solid and innovative company with a strong market presence
• A dynamic, diverse, and multicultural work environment
• Leaders with deep market knowledge and strategic vision
• Continuous learning and development

The new ML Ops team will be our centralized shared services team supporting all ML Ops capabilities such as training, deployment, monitoring and feature stores. They will be responsible for the strategy and implementation of these capabilities as well as best practices for the business units to follow.

• Deliver specific ML Ops engineering tasks such as moderate to complex design, development, implementation, optimization, and maintenance of models, systems, and applications using existing and emerging technology platforms.
• Collaborate with cross‑functional architecture teams to define and integrate frameworks and roadmaps for machine learning solutions, with projects generally of moderate complexity.
• Consult on the design, development, and implementation of DevOps and ML Ops pipelines. May lead portions of deployment processes under guidance from a people leader. Review, verify, validate, and troubleshoot code to ensure high availability and high performance of machine learning models and applications.
• Apply complex knowledge of code‑management principles and best practices to follow architectural and governance guidelines.
• Effectively communicate and apply machine learning engineering value, concepts, and strategies across multiple scenarios.

• 3–6 years of experience in a similar role
• Bachelor's degree in management information systems, computer science, or a related field
• Insurance experience (desirable)
• Fluency in English

• AWS (MUST)
• MLOps experience (understanding models, architecture) (MUST)
• Python (MUST)
• SQL (MUST)
• DataBricks (very desirable)
• Snowflake (desirable)
• Jenkins (desirable)
• ETL pipelines—understanding required
• Independent work and self‑driven attitude

• Competitive salary and performance‑based bonuses
• Comprehensive benefits package
• Flexible work arrangements (remote and/or office‑based)
• Dynamic and inclusive work culture within a globally renowned group
• Private health insurance
• Paid time off
• Training and development opportunities in partnership with renowned companies