FBS MLOps Engineer Manager

Das ist der Job

We believe that the foundation of every successful business lies in having the right people with the right skills.

Darum lohnt es sich

By combining international reach with US expertise, we build diverse and high-performing teams that are equipped to thrive in today’s competitive marketplace. That is where we come in - helping Farmers build a winning team that delivers consistent and sustainable results. Capgemini is responsible for managing local payroll and benefits.

The role involves both hands-on work and supervising a team to deliver effective machine learning engineering solutions for a line of business. The position applies in-depth knowledge of policies, procedures, and business objectives to make decisions and guide team.

Supporting and maintaining solutions in production (fixing bugs, make changes as required, maintaining models) Collaborates with cross-functional teams to integrate machine learning and business logic-based solutions into production systems Effectively communicates and applies machine learning engineering value, concepts, and strategies in various scenarios with stakeholders Recruits, hires, and mentors top talent to build a high-performing MLOps team.

Full English Fluency Experience in a leadership role within a fast-paced, technology driven environment Team: Data Scientist, Python Developers, Cross disciplinary (Underwriting, Actuary) 2 Direct Reports Insurance (PLUS), Healthcare, heavily regulated, audit Technical & Business Skills Possesses strong technical aptitude.

Modern Oriented Language: Python (PLUS), Java, Typescripts, Ruby, Rust Familiar with DevOps practices and tools for continuous integration and deployment. (MUST) Experience in Production Support (Maintaining Models, Bug Fixes) MUST Collaborative with other areas, Translate, strong communication Business Logic Model, Real Time execution: Business Logic Based Solutions, writing code to determine system behavior. (MUST) Small volumes of data but fast execution Automated software and Model Testing (how to know model is behaving properly) Benefits This position comes with competitive compensation and benefits package: Competitive salary and performance-based bonuses Comprehensive benefits package Career development and training opportunities Flexible work arrangements (remote and/or office-based) Dynamic and inclusive work culture within a globally reknowned group Private Health Insurance Pension Plan Paid Time Off Training & Development #J-18808-Ljbffr 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.

Since we don’t have a local legal entity, we’ve partnered with Capgemini, which acts as the Employer of Record.

What to expect on your journey with us: 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 This position leads the deployment, implementation, and optimization of machine learning pipelines to solve complex business challenges.

Performs work independently while receiving limited guidance Key Responsibilities Delivers machine learning ops engineering tasks such as deployment, implementation, optimization, and maintenance of machine learning pipelines and models.

Ensures pipelines support efficient data ingestion, preprocessing, model training, validation, deployment and monitoring. Implements scalable and robust machine learning solutions that can handle large volumes of data and complex models. Implements real-time inference with high availability and low latency.

Creates strategic plans within span of control and implements them across one to two business domains. Ensures seamless integration of pipelines with continuous integration and continuous deployment (CI/CD) tools and workflows.

Supervises, coaches, and guides direct reports Uses advanced knowledge of code management principles to follow architectural and governance guidelines Requirements 5 years of experience required in deploying and managing machine learning pipelines, or related work. In-depth knowledge of machine learning frameworks and libraries.