DUTIES & RESPONSIBILITIES
-
Building data ingestion and MLOps pipelines: Utilize tools like MLFlow, DataRobot, Airflow, Docker, and Kubernetes to streamline model development and deployment
-
Orchestrate CI/CD pipelines: Collaborate with DevOps teams to automate the continuous integration and delivery process using GitLab CI or similar tools
-
Machine learning model optimization: review, refactor, and optimize machine learning pipelines for improved performance, scalability, and efficiency, optimization of resource usage. Focus on Machine learning model performance in terms of data ingestion, serving, runtime, defaults, resource usage
-
Containerization and deployment: Containerize machine learning models and orchestrate their deployment, versioning, and monitoring
-
Testing and validation: Develop and automate tests to ensure the quality and reliability of ML models / pipelines
-
Monitoring: Develop and maintain monitoring of ML models
-
Collaboration and documentation: Work closely with cross-functional teams, including data scientists, data engineers, and architects. Document processes and best practices
WHAT WE OFFER
- Working with modern technologies on interesting projects for international clients
- Cutting-edge IT equipment
- Above average days of paid annual leave
- One extra day of annual leave for every year in Valcon
- An extra day off for a birthday
- Additional health insurance policy
- Indefinite term contract
- Flexible work place and working hours