Engineer I
hace 6 días
ML Ops Engineer to join our team.
Our Client is one of the United States' largest insurers, providing a wide range of insurance and financial services products with gross written premiums well over US$25 Billion (P&C). Finally, our Client is part of one the largest Insurance Groups in the world.
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. ML Ops Engineer will support the ML Ops team and will work to build out the strategic ML Ops capabilities along with other engineers on the team. They will need to be proactive, own user stories, and follow engineering best practices from the team engineering
Delivering specific ML Ops engineering tasks such as moderate to complex level designing, developing, implementing, optimizing, and maintaining models, systems, and applications using existing and emerging technology platforms.
Collaborating with cross-functional architecture teams to define and integrate frameworks and roadmaps for machine learning solutions, projects are generally of moderate complexity.
Consulting on the design, development, and implementation of DevOps and ML Ops pipelines. May lead portions of deployment processes under guidance from people leader. Reviews, verifies, validates, and troubleshoots code to ensure high availability and high performance of machine learning models and applications.
Effectively communicating and applying machine learning engineering value, concepts, and strategies across multiple scenarios.
Bachelor's degree in management information systems, computer science or similar
~ Fluency in English
AWS (MUST)
Python (MUST)
SQL (MUST)
Snowflake (Desirable)
Jenkins (Desirable)
ETL Pipelines – Understanding
A competitive salary and performance-based bonuses.
Flexible work arrangements (remote and/or office-based).
Private Health Insurance.
Training & Development opportunities in partnership with renowned companies
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