Key engineering leading POPS :(pipeline operation system) automated framework to
build and deploy analytics workflows in databricks and AWS. This role will work
on MIME: Enterprise-wide entity that intakes and govern all enterprise wide
analytical workflows making sure our analytical workflows are not unfairly
targeting certain demographics (race, gender and zip codes)
Software Engineer Advisor (MLOps Engineer)
An MLOps Engineer is responsible for deploying, monitoring, and
maintaining machine learning models in production environments. This role
bridges the gap between data science and IT operations, ensuring seamless
integration of machine learning models into operational workflows.
The MLOps Engineer works closely with data scientists, software engineers and
DevOps teams to automate and streamline the model lifecycle, from development to
deployment and monitoring.
In addition to Delivery, the MLOps Engineer should have an automation first and
continuous improvement mindset. They should drive the adoption of CI/CD tools
and support the improvement of the tools sets/processes.
Behaviors of MLOps Engineer:
Full Stack Engineers is able to articulate clear business objectives aligned to
technical specifications and work in an iterative, agile pattern daily. They
have ownership over their work tasks, and embrace interacting with all levels of
the team and raise challenges when necessary. We aim to be cutting-edge engineer
– not institutionalized developers.
This position is with Evernorth, a current business within the Cigna Corporation
Key duties and responsibilities:
* Design, develop, and implement MLOps pipelines for the continuous deployment
and integration of machine learning models.
* Collaborate with data scientists and engineers to understand model
requirements and optimize deployment processes.
* Automate the training, testing and deployment processes for machine learning
models.
* Continuously monitor and maintain models in production, ensuring optima