Machine Learning Engineer

Viva (Viva Armenia CJSC)

- Study the best foreign experience and modern approaches in Machine Learning engineering, MLOps, model deployment, and ML system design - Develop, improve, and maintain Machine Learning models and model training workflows - Build reusable ML pipelines for data preparation, training, validation, scoring, and retraining - Develop batch scoring workflows and model-powered APIs when needed - Support model evaluation, benchmarking, testing, and performance monitoring - Support model lifecycle management, including experiment tracking, model versioning, model registry usage, reproducibility, and monitoring - Package ML solutions for practical use and deployment readiness using Docker or similar containerization approaches - Support CI/CD practices for ML projects to improve reliability, automation, and maintainability - Support integration of ML outputs into applications, analytical tools, dashboards, reports, or business processes Implement code quality, testing, logging, documentation, and version control practices in ML projects - Support stable deployment and monitoring of developed models in available technical environments

- Bachelor’s Degree in a technical related field; computer science, engineering, mathematics, or statistics background is a plus - Strong programming skills in Python - Good knowledge of SQL and data manipulation - Good knowledge of Machine Learning algorithms and model evaluation methods - Experience with Python ML-related packages such as pandas, NumPy, scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch, TensorFlow or similar - Experience with building training, validation, scoring, and retraining workflows - Experience with API development using FastAPI, Flask, or similar frameworks would be a plus - Practical understanding of Docker-based packaging and deployment of Python/ML solutions - Understanding of CI/CD principles for ML or software projects - Knowledge of experiment tracking, model versioning, and model registry tools such as MLflow or similar - Knowledge of model monitoring, logging, testing, and reproducibility practices - Familiarity with containerization (Docker), workflow orchestration tools (like Airflow or Prefect), or local cluster management (Kubernetes) for ML pipelines would be a plus - Knowledge of LLMs, RAG, or AI application development would be a plus - Ability to write clean, maintainable, and documented code - Ability to work independently and collaboratively - Excellent knowledge of Armenian, Russian, and English languages

Apply here https://vivaarmenia.spark.work/career/job/193?lang=am Please mention in your application that you have learned about this position from MyJob.am