Description

You will support the development and deployment of AI pipelines across the full lifecycle, from data engineering to model monitoring.

Responsibilities

• Deploy pipelines for data engineering, model training, fine-tuning, and optimization.
• Build reusable enterprise-grade software components to accelerate ML model delivery.
• Maintain infrastructure and automate processes to support MLOps best practices.
• Collaborate with data scientists and software engineers on high-visibility AI projects.
• Apply data-centric AI development practices using a modern cloud stack.

Required Skills

• Bachelor’s Degree in Computer Science, Data Science, Software Engineering, or a related field.
• Proficiency in Python and at least one other language such as Java, SQL, or Scala.
• Experience with DevOps tools including Jenkins, GitHub, and XMake.
• Hands-on experience with Jupyter, Docker, Kubernetes, and Terraform.
• Understanding of AI/ML concepts including Deep Learning, GenAI, and the ML lifecycle.
• Knowledge of Python libraries and frameworks such as Numpy, Pandas, Keras, scikit-learn, TensorFlow, or PyTorch.
• Strong written and oral communication skills in English.
• Must have at least 3 semesters remaining in your studies.
• Must be able to work from the Walldorf office.

Preferred Skills

• Python backend development using FastAPI, Postgres, or OpenAPI.
• Experience with MLOps tools like mlflow or writing tests for ML models.
• Experience with Hyperscaler offerings.

Key Skills

Education

Any Gradute