Description
5+ years of experience working in a Data Science/Machine Learning Engineering role
Proficient in Python and SQL
Experience deploying and configuring applications in Kubernetes
Experience automating cloud resource deployment in Terraform
Comfortable operating in a Linux environment
Experience building model training pipelines in the cloud(AWS)
Experience deploying ML services and applications to at least one major cloud platform (AWS)
Proficient in software design patterns (eg understand object-oriented and functional programming, inheritance, writing abstract, reusable, and modular code)
Experience building and deploying microservices as part of Machine Learning/Data Science applications
Experience with building continuous integration and delivery pipelines for Machine Learning applications
Preferred:
Experience with at least one deep learning framework (e.g., TensorFlow, PyTorch, Caffe, MxNET)
Experience with Kubeflow, Sagemaker, MLFlow
Experience orchestrating the deployment and management of predictive models in a cloud environment.
Experience working in an AGILE development team.