Machine Learning Engineer

About the role

Promtior is seeking a Machine Learning Engineer to join its Engineering team and help scale its Agentic AI solutions worldwide. You will work on end‑to‑end model development, from data preparation to production deployment, collaborating closely with product and engineering colleagues.

Key responsibilities

• Design, develop, and deploy supervised and unsupervised machine‑learning models in production.
• Process, clean, and engineer features from complex datasets.
• Build and maintain training, validation, and model‑serving pipelines.
• Integrate models with APIs and backend services.
• Contribute to scalable data and ML system architecture design.
• Monitor model performance in production and drive continuous improvements.
• Implement MLOps best practices, including versioning, testing, deployment, and monitoring.

Required profile

• Hands‑on experience developing and productionizing ML models.
• Strong command of Python and major ML libraries (e.g., scikit‑learn, TensorFlow, PyTorch).
• Experience with data pipelines, ETL, and feature engineering.
• Proficiency deploying models on cloud platforms such as AWS, GCP, or Azure.
• Good knowledge of APIs, backend integration, and collaborative Git workflows.
• Advanced English proficiency.

Required skills

• Python
• scikit‑learn
• TensorFlow
• PyTorch
• AWS
• GCP
• Azure
• Git
• NLP
• Computer vision
• LLMs, embeddings, RAG
• MLflow
• Kubeflow
• SageMaker
• Spark
• Ray
• Hyperparameter tuning
• Data engineering
• Distributed processing

What we offer

• 20 paid days off per year.
• Hybrid work model with flexibility.
• Monthly team activities (Flex Days).
• Professional development courses and internal clubs.