MLOps Engineer – Enterprise AI Platform

This is a fully remote position, open to applicants in Poland.

📋 Description

• Develop, automate, and enhance production-grade AI and Machine Learning solutions.

• Convert ML models into dependable, scalable, and production-ready services.

• Utilize contemporary cloud-native technologies.

• Automate machine learning workflows.

• Optimize model deployment processes.

• Assist in building enterprise-level AI infrastructure.

• Collaborate with Data Scientists, ML Engineers, and Cloud Engineers.

• Ensure that machine learning systems are effectively deployed, monitored, and maintained.

⛳️ Requirements

• A minimum of 2 years of practical experience in MLOps, DevOps, Cloud Engineering, Machine Learning Engineering, or a similar field, with hands-on exposure to ML deployment or workflows.

• Proficient in Python programming, with the ability to write clean, maintainable, and testable code.

• Practical experience with Docker and deploying applications in Kubernetes environments.

• Hands-on experience with at least one major cloud provider: Azure, AWS, or GCP.

• Experience with automated build, test, and deployment pipelines using tools like GitLab CI, GitHub Actions, or similar solutions.

• Understanding of ML workflows, model deployment, experiment tracking, and model lifecycle management.

• Familiarity with at least one orchestration tool, such as Kubeflow Pipelines, Apache Airflow, or Argo Workflows.

• Practical knowledge of Terraform or similar Infrastructure as Code tools.

• Familiarity with monitoring and logging tools such as Prometheus, Grafana, or equivalent solutions.

• English proficiency at B2+ level, adequate for technical discussions, documentation, and daily collaboration in an international setting.

• Nice to have: Experience with MLflow, including experiment tracking and model registry.

• Nice to have: Familiarity with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.

• Nice to have: Experience with model serving technologies such as KServe, NVIDIA Triton Inference Server, vLLM, or ONNX Runtime.

• Nice to have: Knowledge of GitOps and deployment automation using Argo CD or Argo Rollouts.

• Nice to have: Experience with data drift detection, model monitoring, or ML observability tools.

• Nice to have: Familiarity with Apache Kafka, Apache Spark, or distributed data processing.

• Nice to have: Knowledge of GPU-based ML workloads, distributed training, or inference optimization.

• Nice to have: Experience with feature stores like Feast or data versioning tools like DVC.

• Nice to have: Understanding of cloud security, IAM/RBAC, and secrets management.

🏝️ Benefits

• Opportunity to work with cutting-edge technologies in machine learning and high-quality software development.

• Annual budget for self-development.

• Ability to contribute to a diverse range of exciting projects.

• Access to internal workshops.

• Personal branding opportunities (articles, conference speaker, internal workshop leader).

• Flexible working hours.

• Option for remote work.

• Chillout room, free beverages, and team & company events.

• Supportive atmosphere.

• MultiSport membership.

• LuxMed health services.