AI Platform Engineer

We are seeking an experienced AI Platform Engineer to design and maintain the infrastructure that powers machine learning and AI systems at scale. You will build the internal platforms and tools that enable data scientists and engineers to train, deploy, and monitor models efficiently. This role focuses on building reliable, scalable, and secure AI infrastructure.

Details

Location: Remote (Europe)
Employment Type: Full-time / Contract
Start Date: ASAP
Language Requirements: English – Upper-Intermediate or higher

Key Responsibilities

Design and maintain AI/ML platforms and infrastructure for model development and deployment.

Build scalable pipelines for training, serving, and monitoring machine learning models.

Implement MLOps best practices including CI/CD pipelines for AI systems.

Optimize compute infrastructure for model training and inference workloads.

Ensure reliability, scalability, and observability of AI services.

Work closely with data scientists and AI engineers to improve productivity and platform usability.

Maintain security and compliance standards for AI infrastructure.

Requirements

4+ years of experience in software engineering or DevOps.

Strong experience with Python, Go, or similar backend languages.

Experience with containerization and orchestration (Docker, Kubernetes).

Familiarity with MLOps frameworks and tools.

Experience building data pipelines and distributed systems.

Knowledge of cloud platforms (AWS, GCP, Azure).

Strong understanding of system scalability and performance.

Nice to Have

Experience with Kubeflow, MLflow, Airflow, or similar platforms.

Familiarity with GPU workloads and distributed training systems.

Experience working with vector databases or LLM infrastructure.

Knowledge of observability tools such as Prometheus and Grafana.

Background supporting data science teams.