Junior ML Engineer

We’re looking for a Junior ML Engineer to join our client’s R&D team and grow your expertise in bringing modern ML solutions into production.
 

• 1.5+ years of experience working with ML models or data pipelines in Python
• Familiarity with the ML lifecycle, from data preprocessing and feature engineering to training and evaluation
• Practical experience with ML libraries such as scikit-learn, pandas, NumPy (experience with PyTorch or TensorFlow is a plus)
• Knowledge of MLOps concepts (MLflow, SageMaker, Kubeflow, or similar tools)
• Understanding of cloud platforms (AWS/GCP/Azure) and containerization (Docker)
• Experience with Git, unit testing, and CI/CD workflows (even on a small scale)

• English: Upper-Intermediate or higher

   

Nice to have:

• Exposure to real-time model monitoring, model drift, or A/B testing
• Familiarity with data pipeline orchestration tools (Airflow, Prefect, Dagster)

• Understanding of distributed systems (Spark, Ray) or vector databases

   

Responsibilities

• Support the design and development of ML pipelines for classical ML and LLM-based models
• Contribute to data preprocessing, feature extraction, and model training workflows
• Assist in deploying ML models to cloud environments (AWS/GCP/Azure) using Docker or similar tools
• Help maintain monitoring and logging for model accuracy and performance
• Collaborate with data scientists and backend engineers to integrate ML solutions into production
• Learn and apply MLOps best practices, reproducibility, CI/CD, and monitoring
• Participate in code reviews and continuous improvement of engineering processes