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.
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. Supervises, coaches, and guides direct reports
Uses advanced knowledge of code management principles to follow architectural and governance guidelines

5 years of experience required in deploying and managing machine learning pipelines, or related work.
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
Possesses strong technical aptitude. In-depth knowledge of machine learning frameworks and libraries.
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) **

MLOps Engineer Manager

Key skills