DataArt Armenia

Job description:

DataArt is a global software engineering firm. With over 20 years of experience, teams of highly-trained engineers around the world, deep industry sector knowledge, and ongoing technology research, we help clients create custom software that improves their operations and opens new markets. DataArt started out as a company of friends and has a special culture that distinguishes it from other IT outsourcers, such as:

- Flat structure. There are no “bosses” and “subordinates”.

- We hire people not to a project, but to the company. If the project (or your work in it) is over, you go to another project or to a paid “Idle”.

- Flexible schedule, ability to change projects, to work from home, to try yourself in different roles.

- Minimal bureaucracy and micromanagement, convenient corporate services.

/en/mlops-engineer

Required qualifications

• Experience in administering cloud-based platforms (AWS, GCP, Azure)
• Understanding the principles of building distributed and serverless systems
• Knowledge of components and services of one or more cloud-based platforms (AWS, GCP, Azure)
• Understanding the main principles of container-based platforms and tools
• Experience working with/administering Kubernetes in its various flavours (e.g. on-prem, AWS EKS, Google K8s, Azure, OpenShift )
• Experience in implementing infrastructure as code (e.g. Terraform, AWS CloudFormation, GCP Cloud Deployment Manager, Helm)
• Experience with/theoretical understanding of building continuous delivery/continuous deployment
• Knowledge of development methodologies, particularly with Agile/Scrum
• Good spoken English

Nice to Have

• Understanding of general ML/AI landscape and major areas of applications
• Understanding of typical ML/AI software development lifecycle (e.g. experiment management, model training, hyperparameters optimisation, model serving)
• Knowledge/theoretical understanding of typical ML tools and frameworks (e.g. Jupyter, TensorFlow, Keras, Pytorch, Katib, etc.)
• Experience with one or more MLOps platforms (AWS Sagemaker, Google AI TFX, Kubeflow, MLFlow, Domino Labs, neu.ro etc.)
• Experience with orchestration/configuration management tools (Ansible, Chef, etc.)
• Main cloud providers’ certification (AWS, Azure, GCP)

Required candidate level: Mid level

Additional information