AI/ML Engineer – GenAI & Production ML

Poland and Middle-Eastern Europe; Poland; On-site; PLN 180,000 - 240,000; Full time

Job summary

Xebia is seeking a Mid AI/ML Engineer to join our team delivering end-to-end AI and Generative AI solutions across dealer operations and data platforms. You will own ML lifecycle components from data preparation to production deployment, collaborating with data engineers, MLOps, and business stakeholders to transform needs into production-ready AI.

Ideal candidates have 3–6 years in ML/AI engineering, hands-on with PyTorch/TensorFlow, MLflow, and cloud platforms (Azure ML preferred; Vertex

Qualifications

• 3–6 years of professional experience in Machine Learning / AI Engineering.
• Hands-on with PyTorch or TensorFlow and scikit-learn.
• Production-grade ML models and end-to-end ML lifecycle experience.
• Familiarity with MLflow, CI/CD, and MLOps practices.
• Cloud-based ML platforms (Azure ML preferred; Vertex AI or SageMaker welcome).
• Knowledge of governance, documentation, and responsible AI principles.

Responsibilities

• Design and develop ML solutions aligned with business objectives.
• Build, train, evaluate, and deploy ML models for analytics and decision support.
• Own the ML lifecycle: data prep, feature engineering, training, deployment, monitoring.
• Collaborate with Data Engineers, MLOps Engineers, Architects, and stakeholders.
• Support CI/CD, observability, model governance, and continuous improvement.

Skills

ML Engineering

PyTorch

TensorFlow

scikit-learn

MLflow

Azure ML

SageMaker

Vertex AI

CI/CD

MLOps

Data wrangling

Communications

Tools

MLflow

Azure ML

Vertex AI

SageMaker

PyTorch

TensorFlow

scikit-learn

CI/CD tools

Job description

Xebia is seeking a Mid AI/ML Engineer to join our team delivering end-to-end AI and Generative AI solutions across dealer operations and data platforms. You will own ML lifecycle components from data preparation to production deployment, collaborating with data engineers, MLOps, and business stakeholders to transform needs into production-ready AI.

Ideal candidates have 3–6 years in ML/AI engineering, hands-on with PyTorch/TensorFlow, MLflow, and cloud platforms (Azure ML preferred; Vertex