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Upvanta sp. z o.o.

AI / MLOps Engineer

Upvanta sp. z o.o. Zobacz wszystkie oferty
Warszawa
Wrocław
Gdańsk
Kraków
Wygasa 9 gru 2026
1 dzień temu

W skrócie

AI/MLOps Engineer sought for designing, deploying, and operating AI platforms. Responsibilities include building ML pipelines, automating workflows, CI/CD, monitoring, and deploying AI using Docker/Kubernetes on Azure, AWS, or GCP. Requires 3+ years of experience and Python skills.

Skrót przygotowany przez AI na podstawie treści ogłoszenia.

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.

Key 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
  • Ensure security, compliance, and operational excellence across AI services
  • Collaborate closely with Data Scientists, DevOps Engineers, Software Developers, and business stakeholders

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

Technologies We Use

  • 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

Nice to Have

  • 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
Opublikowana 2026-11-09
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