LOCATION: KRAKÓW OR REMOTELY FROM POLAND / BARCELONA OR REMOTELY FROM SPAIN
SALARY: up to 35 000 PLN monthly
ABOUT THE ROLE
You will have the opportunity to turn machine learning artifacts into production systems and to participate in implementing state-of-the-art MLOps practices, and to improve your skills in NLP, machine learning, large scale data processing and information retrieval.
WHAT WILL YOU DO?
- Turn machine learning artifacts into production systems, integrated with other product features or business processes.
- Deploy and orchestrate data pipelines transforming raw data into features that are digestible for the ML algorithms and maintain the feature store up-to-date.
- Deploy and maintain the label management system and automate the integration of the data labeling processes.
- Build sanity checks and dashboards for monitoring data quality, model drifts, operational efficiency, and system performances.
- Monitor and identify potential biases and unfair behaviors in model behaviors.
- Work with ML Engineers to deploy and orchestrate robust pipelines for training, evaluation, and inference at scale.
- Build tools for supporting experiments, development, and debugging of machine learning models.
- Create and maintain the infrastructure required for both development and production environments using infrastructure-as-a-code.
- Create automatic workflow for building, testing, tracking experiments, versioning, deployment, using CI/CD tools.
WHAT WILL YOU NEED TO BE SUCCESSFUL IN THIS ROLE?
- 2+ years practical experience and expert knowledge of cloud architectures (AWS, GCP, or Azure), services, and administration best-practices for stability and functionality (depending on seniority).
- 2+ years experience with microservices, REST or GraphQL APIs, load balancing, production web-hosting networking (depending on seniority).
- 2+ years experience with CI/CD pipelines or other code automation techniques (depending on seniority).
- Terraform or other IaaC frameworks (e.g. CloudFormation, SAM, Google Deployment Manager, serverless.com or similar).
- Bash and Unix command line toolkit (e.g. AWS cli or boto3 sdk).
- Fluent in English.
