MLOps Engineer

Quick Facts

• Role: MLOps Engineer

Description

Build and maintain the production infrastructure and processes that help machine learning and AI solutions run reliably, securely, and cost-effectively. Own ML CI/CD workflows (training → validation → deployment/rollback), model registry and experiment tracking, and production monitoring for quality, drift, and resource usage. Contribute to MLOps standards and support GenAI/LLM infrastructure such as model gateways, query routing, and cost control.

Responsibilities

• Ensure training and deployment infrastructure is efficient, available, and properly uses GPU/cloud/on-prem resources.

• Create and evolve CI/CD pipelines for ML models (train, validate, deploy, and roll back).

• Manage model registry, experiment tracking, and versioning of artifacts and features.

• Deploy models to production and build self-service tools/templates to accelerate delivery from idea to rollout.

• Monitor production model performance, including quality changes, drift, and resource utilization; implement alerts and automatic rollback.

• Develop MLOps standards and documentation; support infrastructure for GenAI and LLMs (model gateways, routing, cost control, agent systems).

Requirements

• Practical experience with CI/CD for ML models and maintaining models in production.

• Python, SQL, Docker, and Kubernetes/EKS knowledge.

• AWS experience for ML workloads (e.g., S3 and compute resources).

• MLflow (or similar) for experiment tracking and model management.

• ML pipeline orchestration tools such as Dagster, Airflow, or Kubeflow.

• LLM support tooling such as LiteLLM.

• Snowflake knowledge for efficient and cost-effective data/feature retrieval.

• Git, Terraform, and monitoring tools for services and model quality.

• Ability to explain technical topics simply and to handle unexpected problems; accuracy in environment configuration.

• Polish and English proficiency at least B2.

Benefits

• Private LuxMed medical care, free preventive tests, and spine-relief massages.

• Budget for remote work equipment and gift vouchers.

• On-site breakfast buffet.

• Integration and family trips to a private resort by a lake.

• Multisport card co-financing.

• Team budgets for specialized training and courses tailored to your needs.

• Knowledge sharing via topic guilds organized by colleagues.

• Work in a team focused on experimentation and innovation, with real impact on product and service development.