Required Skills/Experience:
● Know Python, Docker, Cloud engineering, SQL, Basic ML algorithms.
● Comfortable with cloud-based platforms such as Azure Data Factory and Azure ML Pipeline
● Have used version control applications like Gitlab

Preferred Skills/Experience Nice to Have:
● Python ML frameworks: Pytorch, Jupyter Notebooks, Pandas, scikit-learn, Numpy
● Have used PySpark or Azure Databricks Notebooks
● Understand Continuous integration, testing, deployment & release methodologies

With us you can:

Develop your technical knowledge:
— Use latest technologies
— Participate in technical events and conferences (the cost is covered by the company)
— Regular techtalks and professional development

Improve your soft skills:
— Build strong teamwork skills and become an essential part of the dynamic teams
— Improve your English at classes and speaking directly with clients
— Increase your productivity and communication level via Scrum, Kanban, Agile methodologies

What else do we offer?
— Competitive compensation and benefits
— Flexible working schedule
— Remote work or work in one of our development offices
— Covered rest period (20 business days+ 5 days-off)
— Professional growth: a variety of projects, regular technical events, mentorship.
— Free English classes (we have an amazing English teaching team)
— Speaking-club with a native English speaker
— Truly friendly atmosphere and teambuilding

Core Responsibilities:
● Manage the whole machine learning lifecycle
● Create automated ETL pipelines for training datasets
● Create a ML pipeline to train, evaluate and deploy models
● Collaborate with engineering and product development teams to productionize the developed AI model