AI / MLOps Engineer
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Salary
$70k per year
Location
In office (Kraków)
Employment
Contractor
First seen by Alion on Nov 6, 2026.
Overview
Company
Impact
Profile match
Upvanta is a Polish technology company that combines software development services with recruitment, supplying engineers and delivery teams to clients in Poland and western Europe. It works on custom application development, cloud and infrastructure engineering, data platforms and quality assurance, staffing those projects both from its own bench and through placements sourced for the client directly. The company is based in Warsaw, advertises a continuous board of technology vacancies under its own name, and works across financial services, retail and industrial accounts.
We are looking for an experienced AI / MLOps Engineer to help design, deploy and operate production-grade AI platforms and machine learning solutions.If you are passionate about Machine Learning, Cloud technologies, automation, and modern AI operations, we'd love to hear from you.
Zakres obowiązków
- 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
- Ensure security, compliance, and operational excellence across AI services
- Collaborate closely with Data Scientists, DevOps Engineers, Software Developers, and business stakeholders
Wymagania
Required Skills- 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
- 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
- Experience with Generative AI (GenAI), Large Language Models (LLMs), or Agentic AI solutions
- AI, Machine Learning, Cloud, or Kubernetes certifications
- Experience working in large-scale enterprise environments
- Knowledge of Responsible AI, MLOps governance, and model lifecycle management
Tech stack
- AI
- MLOps
- Machine Learning
- Python
- AWS
- GCP
- Docker
- Kubernetes
- CI/CD
- Agile
- TensorFlow
- PyTorch
- scikit-learn
- MLflow
- Kubeflow
- Apache Airflow
- Microsoft Azure
- Google Cloud Platform
- Apache Spark
- Apache Kafka
- Terraform
- Prometheus
- Grafana
- LLMs
- Cloud
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