ML Engeneer (MLOps)
Условия работы
Responsibilities:
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Develop and maintain ML pipelines (from model training to production deployment);
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Build REST APIs for models using FastAPI/Flask;
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Containerize applications (Docker) and manage infrastructure (docker-compose, Kubernetes);
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Set up CI/CD for ML projects (GitHub/GitLab Actions, Jenkins);
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Monitor models in real time (MLflow, Weights & Biases);
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Integrate with cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML Studio);
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Automate ETL processes (Airflow, Prefect);
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Participate in code reviews and collaborative development.
Requirements:
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Strong proficiency in Python (OOP, clean code principles);
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Experience writing unit and integration tests;
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Libraries: NumPy, Pandas, Scikit-learn + PyTorch/TensorFlow;
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Docker (images, Dockerfile, docker-compose);
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Cloud platforms: AWS (S3, EC2), GCP (Cloud Storage), Azure (Blob Storage);
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CI/CD tools: GitHub/GitLab Actions, Jenkins;
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Experience with MLflow, Weights & Biases;
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Ability to monitor models in production;
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Strong problem-solving skills for complex technical tasks;
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Effective communication with Data Scientists, developers, and Product Managers;
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Willingness to quickly learn new MLOps technologies;
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Experience with Kubernetes (Pods, Services, ConfigMaps);
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Familiarity with DVC or MLflow integration;
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Experience setting up ETL pipelines (Airflow/Prefect).
What we offer:
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Work schedule: 5 days a week, from 9:00 AM to 6:00 PM;
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Employment in accordance with the Labor Code of the Republic of Uzbekistan, with 28 calendar days of paid vacation;
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No strict dress code — we aim to break stereotypes about government organizations;
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Work in a strong team of professionals willing to share knowledge and experience;
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Opportunity to participate in major, impactful projects aimed at improving quality of life and optimizing business processes at leading enterprises in the country;
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Broad autonomy and real influence over the company’s development.
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