Institute of Smart Systems and Artificial Intelligence is looking for MLOps Engineer. 

Responsibility:
- deploying, monitoring, and maintaining machine learning models in production environments;
- working closely with data scientists;
- ensuring seamless integration of machine learning models into operational workflows;
- managing GitHub and Hugging Face repositories (datasets, models, and spaces).

Required skills and experience
● At least 2 years of experience in MLOps, DevOps or a related field.
● At least Bachelor’s degree in Computer Science, Data Science or a related
field.
● Proficiency in Linux based operating systems.
● Strong understanding of machine learning principles and model lifecycle
management.
● Proficiency in programming languages such as Python, with hands-on
experience in machine learning frameworks like TensorFlow, PyTorch, or
Scikit-learn.
● Experience with working on the Hugging Face platform.
● Knowledge of CI/CD pipelines, automation tools and version control
systems like Git.
● Familiarity with containerization and orchestration tools such as Docker
and Kubernetes.
● Experience with monitoring tools and practices for model performance in
production (WandB, Tensorboard).
● Ability to work collaboratively in cross-functional teams.
● Knowledge of SQL would be a plus.
● Experience with cloud platforms like AWS, Azure, or Google Cloud and their respective machine learning services would be a plus.