AI Data Engineer

Quick Facts

• Role: AI Data Engineer

Description

You will prepare and analyze data from multiple sources to develop and optimize (Agentic) AI and machine learning models. You will design, implement, and operate software solutions for structured and unstructured data, with the goal of achieving a highly automated ML lifecycle. You will also support operational teams with AI model integration and design/pilot monitoring and evaluation for implemented AI use cases.

Responsibilities

• Prepare and analyze data from multiple sources to develop and optimize (Agentic) AI and machine learning models
• Design and standardize scalable AI environments, AI blueprints, and processes
• Design, implement, and operate software solutions for structured and unstructured data, particularly for (Agentic) AI and machine learning
• Develop technical know-how, tools, and methods for (Agentic) AI
• Support operational units in implementing AI models into existing processes and systems to maximize value
• Design and pilot AI solutions to monitor and evaluate outcomes of executed and implemented use cases

Requirements

• Fluency in English
• Completed degree in computer science, artificial intelligence, or data
• Sound knowledge of GenAI, machine learning, deep learning, relevant algorithms/models, and RAG
• Experience preparing, cleansing, and enriching data for AI applications
• Very good knowledge of one or more programming languages (preferably Python), including AI frameworks (e.g., PyTorch)
• Knowledge of SQL for managing and querying data
• Experience with tools/frameworks for training, deploying, and monitoring AI models, including MLOps practices
• Familiarity with distributed systems and cloud platforms for scaling AI applications (e.g., Azure, Databricks, Kubernetes)
• Strong ability to identify and analyze data patterns and develop prediction/decision-making models
• Ability to collaborate with interdisciplinary teams and communicate complex technical concepts clearly
• Strong service orientation, excellent teamwork skills, and commitment to business needs
• Familiarity with Git: create proper pull requests and perform code reviews

Benefits

• Medical package, sports card, and numerous sports sections
• Flexible working hours, confidential employee assistant program, and remote working option
• Workshops and training courses, hackathons and meetups, digital learning platforms, and language courses
• Annual CSR activities
• Team-building activities such as company-wide bike races and soccer matches, and other events
• Diversity and inclusion across gender, nationality, beliefs, disability, age, and sexual orientation or identity