As an MLOps engineer on our team, you will help deploy, maintain, and monitor our AI and ML solutions across a variety of client spaces.
You will be responsible for generating and managing reusable CI/CD pipelines that allow our infrastructure to be rapidly prototyped and deployed.
You’ll utilize cloud-native and open-source frameworks to allow our software to be automatically and continuously tested, built, and deployed.
This opportunity will allow you to become an integral part of an agile team by cutting down time spent on manual testing, debugging, and deployment.
In doing so, our team will become more responsive and efficient to ever-changing client needs, while also becoming empowered to ship robust AI and ML products.
Expand your experience with MLOps on an incredibly talented and collaborative team.
Requirements & Skills:
10+ years of experience with machine learning, DevOps, data science, or software engineering
Experience building and deploying containerized ML solutions with Docker and Kubernetes
Experience with cloud platforms, including AWS, Google Cloud, or Azure
Experience with ML programming languages, including Python, Scala, or Java
TS/SCI clearance; willingness to take a polygraph exam
