About The Role
At Flo we go from idea to production in minutes. In this role you own the end-to-end Machine Learning Pipeline together with CI/CD for our ML Engineering process. You focus on code, versioning of datasets, models and production endpoints to allow ML Engineers to collaborate, experiment and scale fast.
- ML Pipeline Automation.
- Continuous Integration for Machine Learning projects.
- Continuous Delivery for Machine Learning projects.
- Improve and advance DataOps and MLOps infrastructure and operational processes.
- 4+ years of industry experience in applied ML.
- Strong proficiency with Python, Scala and/or Go.
- Experience with AWS or other cloud providers.
- Experience with Jenkins or other build tools.
- Experience with ML Inference servers such as Triton, KFServing, or Seldon Core.
- Experience with Kubeflow, MLFlow or Sagemaker.
- Experience with infrastructure as code tools such as Terraform, Cloudformation, Ansible, Puppet or Chef.
- Experience with Kubernetes.
- Experience with Spark and/or databricks.
- Experience at the tier 1 product company or related experience working within the product organization.