Software Engineer - Machine Learning Infrastructure

The Team

Celonis AI Group (CeloAI) is a newly formed organization within Celonis that is dedicated to developing state-of-the-art AI/ML (and broadly intelligent) technologies for Celonis products (e.g., the Execution Management System / EMS) and empower enterprises and institutions to make intelligent business decisions and achieve operational excellence. Our dual mission focuses on both the immediate term goals of designing and implementing advanced AI/ML product features and solutions for our customers and the long term goals of establishing competitive advantages of Celonis for execution management.

We are a global organization with presence in both Germany and the US. CeloAI Germany has its presence in Munich, Darmstadt, and Aachen.

The Role

As a software engineer (machine learning) of the infrastructure team, you are responsible for designing and developing external and internal solutions, along with the underlying infrastructure, that will accelerate AI/ML/LLM product development. You may interact closely with other software engineers, machine learning engineers and platform infrastructure engineers within the product and engineering organization to build scalable and high quality AI/ML/LLM solutions for our customers.

You may also be responsible for designing and implementing new foundational technical components that will power the next generation of EMS and elevate the impact Celonis has on our customers. These components may span the areas of computer vision, natural language processing, data mining, recommendation, knowledge base, business intelligence, and other AI technologies.

The work you’ll do

• Deeply understand the business and technical requirements
• Design and develop scalable solutions
• Design and build robust and low latency infrastructure to serve the AI/ML/LLM models and meet the demands of Celonis customers
• Design and develop intelligent techniques to understand, represent, and integrate enterprise operational data (e.g., processes)
• Design and build APIs, libraries and infrastructure to serve such data at scale and with low latency
• Design and implement intelligent ways to ensure freshness and accuracy of such data across thousands of enterprise customers.

The qualifications you need

• 5+ yrs of experience in software engineering or a relevant technical role (preferably experienced in Machine Learning Ops)
• You have a good understanding of DevOps tools and technologies such as: Kubernetes, Terraform, DataDog, Docker, CI/CD
• You are experienced with Cloud Provider solutions (AWS, Azure, GCP)
• You are comfortable designing, building, documenting and distributing robust and scalable solutions in the form of services, libraries and tools
• You are passionate about developing AI/ML/LLM solutions