ML Platform Engineer (AI)

Location: Remote from Germany or onsite in Würselen near Aachen; occasional travel for team events and onsite work.

Company

hirify.global develops Cadmould, an advanced plastic injection molding simulator, and the Cadmould AI Solver, a transformer-based Large Engineering Model for high-fidelity simulation.

What you will do

• Build and own the training and data platform, including versioning, traceability, reproducibility, and lineage.
• Develop the model lifecycle from experimentation to production, including model versioning, registry, promotion, training, and deployment.
• Implement monitoring for model degradation and incoming data drift.
• Provide workflows and tooling for AI engineers and data scientists to train, evaluate, and deploy models.
• Operate and scale the AWS service that serves AI models, including support for multiple selectable, access-controlled, or user-specific models.
• Design interfaces and rollout plans together with the Cloud team, contributing to software and infrastructure engineering where needed.

Requirements

• Background in Computer Science, Data Engineering, Machine Learning, or a related field, with 3+ years of relevant experience.
• Strong Python skills and solid software engineering fundamentals, including testing, version control, and CI/CD.
• Hands-on experience taking ML systems from training into production, including data pipelines, training workflows, and deployment.
• Experience with cloud environments and containerization such as AWS, Docker, or Kubernetes.
• Familiarity with experiment tracking and model or data versioning tools such as MLflow, Weights & Biases, or DVC.
• English is the working language; German is a plus.

Nice to have

• Experience with scientific computing or simulation data.
• Experience deploying AI models to CPU-only on-premises or edge targets and hybrid environments.
• Workflow orchestration with Airflow, Prefect, or similar tools.
• Inference optimization through quantization, pruning, or efficient architectures.
• AWS services such as S3, EC2, ECR, or SageMaker, plus Terraform.
• Experience building internal platforms or tooling for other engineers.

Culture & Benefits

• Work on a technical challenge combining simulation, cloud, and AI.
• High ownership and direct product and business impact in a company of about 40 people.
• Modern tools including Notion, GitHub, Linear, and coding agents.
• Direct, honest feedback and a non-micromanaged working environment.