Comarch SA

MLOps Engineer (DevOps / Platform / SRE background)

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SeniorZdalnie·KrakówFull-time

#412064·Dodano dwa miesiące temu·12

Źródło: Comarch

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Tech Stack / Keywords

Inżynier systemowyMachine LearningAIMLKrakówKatowiceKielceSeniorRegularDoświadczeni programiści

Podsumowanie oferty

As an MLOps Engineer, you will design and scale AI systems by managing compute infrastructure and automating the machine learning lifecycle. The role involves working with Docker, Kubernetes, and infrastructure as code tools in cloud environments such as AWS, Azure, or GCP. You will collaborate closely with ML Engineers and Data Scientists to enforce production best practices. This opportunity includes maintaining production-grade ML model environments and contributing to global financial products.

Wymagania

Minimum 2–3 years of hands-on experience as a DevOps Engineer, Platform Engineer, SRE, or similar role.
Strong expertise in Docker and Kubernetes.
Hands-on experience with Infrastructure as Code, especially Terraform, and building CI/CD pipelines using GitLab CI, GitHub Actions, or Jenkins.
Solid knowledge of at least one cloud platform: AWS, Azure, or GCP.
Proficiency in scripting with Python, as well as Bash and HCL.
Understanding of ML model lifecycle and hardware resource allocation (CPU/GPU/TPU) with initial hands-on AI/ML project experience.
Fluent English communication skills (minimum B2 level).

Nice to have:

Experience with model hosting and inference servers like KServe, vLLM, NVIDIA Triton Inference Server.
Hands-on with MLOps platforms such as Kubeflow, MLflow, and DVC.
Experience with monitoring and logging tools including Prometheus, Grafana, ELK Stack, and OpenTelemetry.
Higher education degree, preferably in Computer Science or related fields.

Obowiązki

Key Responsibilities:

Build and maintain scalable, production-grade environments for training and serving ML models using Docker, Kubernetes, and cloud platforms.
Design and automate the complete machine learning lifecycle including testing, training, validation, and production deployment.
Define and manage cloud resources using Infrastructure as Code tools like Terraform or CloudFormation.
Implement monitoring systems for model performance, detecting data/concept drift, and real-time alerting with tools like Prometheus and Grafana.
Deploy tools for versioning models, experiments, and datasets, such as MLflow and DVC.
Collaborate with ML Engineers and Data Scientists to define and enforce production best practices.

Benefity

Develop advanced AI features for digital products used by FinTech and global banking leaders.
Work with a modern technology stack and a safe environment for experimentation.
Access certifications, training, conferences, and internal workshops led by senior AI and MLOps professionals.
Hybrid work model post-onboarding: 60% office presence in Kraków/Katowice and 40% remote.
Comprehensive private medical care coverage for employees and their families.
Supportive culture with sports initiatives, integration events, and community activities promoting active lifestyles.

Elastyczne godziny

Opieka zdrowotna

Dofinansowanie szkoleń

Budżet konferencyjny

Karta sportowa

Spotkania integracyjne

Comarch SA

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