AI & MLOps Engineer: Build Production ML Pipelines

Upvanta; Kraków; On-site; PLN 180,000 - 250,000; Full time

Job summary

Upvanta is seeking an experienced AI / MLOps Engineer to design, deploy and operate production-grade AI platforms and machine learning solutions in a Kraków-based role.

Ideal candidates will have strong Python skills, hands-on deployment experience, and practical knowledge of cloud platforms (Azure/AWS/GCP), Docker, Kubernetes, and CI/CD practices. The role emphasizes Agile collaboration and scalable ML workflows.

Qualifications

• 3+ years of experience in AI/ML Engineering, MLOps, Machine Learning Engineering, or related roles.
• Strong Python programming skills.
• Experience deploying ML models into production environments.
• Hands-on experience with Azure, AWS, or GCP.
• Solid knowledge of Docker, Kubernetes, and CI/CD practices.
• Experience with monitoring and observability tools.
• Understanding of software engineering best practices and infrastructure automation.
• Experience working in Agile environments.

Responsibilities

• Design and implement scalable ML pipelines for training, deployment, and monitoring.
• Automate data ingestion, preprocessing, and feature engineering workflows.
• Integrate AI/ML models into enterprise applications and APIs.
• Develop and maintain CI/CD pipelines for Machine Learning systems.
• Monitor model performance, detect model drift, and automate retraining processes.
• Deploy AI workloads using Docker and Kubernetes.

Skills

AI

MLOps

Python

Cloud

LLMs

Agile

3+ years experience

Tools

Python

TensorFlow

PyTorch

Scikit-Learn

MLflow

Kubeflow

Apache Airflow

Docker

Kubernetes

Microsoft Azure

AWS

Google Cloud Platform (GCP)

Apache Spark

Apache Kafka

Terraform

Prometheus

Grafana

Job description

Upvanta is seeking an experienced AI / MLOps Engineer to design, deploy and operate production-grade AI platforms and machine learning solutions in a Kraków-based role.

Ideal candidates will have strong Python skills, hands-on deployment experience, and practical knowledge of cloud platforms (Azure/AWS/GCP), Docker, Kubernetes, and CI/CD practices. The role emphasizes Agile collaboration and scalable ML workflows.