Become our new Junior AI Engineer (m/f/d)
Are you passionate about AI and cutting-edge technologies? Do you want to help companies leverage AI to create real business impact? Are you ambitious, solution-oriented, and eager to work at the intersection of data engineering, machine learning, and cloud technology? Then join our team at KI performance!

EDUCATION:

• Bachelor’s or master’s degree in computer science, artificial intelligence, or a related field.

WHY JOIN US?

• Exciting AI projects - with cutting-edge technologies – work with Azure, Databricks, OpenAI, and more.
• High-performance culture – we’re looking for “Doers” who want to make an impact.
• Fast learning & career growth – benefit from top-tier training and certifications.
• Innovative company culture – we embrace hands-on mentality, team spirit, and AI-driven excellence.
• Broad ecosystem – as part of our DNA, we cultivate an exceptional network and work closely with partners and startups.

YOUR ROLE AS AN AI ENGINEER

As a Junior AI Engineer, you play a key role in designing and implementing state-of-the-art AI solutions. You are responsible for the entire AI lifecycle - from data ingestion and transformation to building, deploying, and optimizing machine learning models. You work closely with data platform teams and ensure that AI-driven insights translate into tangible business value.
With a strong focus on innovation, scalability, and operational excellence, you stay up to date with the latest AI advancements (e.g., Multiagent-Architectures) and cloud technologies on Microsoft Azure.

YOUR RESPONSIBILITIES

• End-to-End AI Development – Build and optimize AI models, covering the entire lifecycle from data ingestion to deployment and operations.
• Machine Learning & Advanced Analytics – Apply statistical and ML concepts to solve business challenges, including predictive analytics, optimization, and NLP.
• Generative AI - Build, integrate and optimize Large Language Models (LLM), including Text-to-Speech (TTS), Speech-to-Text (STT).
• Data Engineering & Pipelines – Ensure data quality by handling ingestion, preparation, and transformation to create a solid foundation for AI use cases.
• AI Deployment & Operations – Implement scalable and production-ready AI solutions using cloud-based MLOps best practices.
• AI Innovation – Stay up-to-date with the latest advancements in AI and cloud technologies, and evaluate their potential for integration.
• Customer Enablement & Integration – Collaborate with cross-functional teams to customize AI tools and embed them into business processes for maximized value.
• Compliance & Governance - Ensure compliance with data privacy, security, and ethical AI guidelines in all solutions.