T Hub - AI Engineer

Working at T-Mobile’s T Hub will offer you an unique and highly rewarding experience on IT market. As a leader in the telecommunications industry, T-Mobile not only provides a platform to hone your technical skills but also empowers you to be a catalyst for innovation. You'll have the opportunity to work at the forefront of cutting-edge technologies, from 5G to IoT and AI, shaping the future of connectivity. Our commitment to fostering a diverse and inclusive workplace means you'll collaborate with a wide range of talented professionals, learning and growing together. T-Mobile encourages a culture of continuous learning and development, offering mentorship and support to help you thrive in your career.

• Minimum 5 years in software engineering or machine learning roles with strong AI focus
• English language proficiency B2 or above. German language skills would be beneficial but not essential
• Expert in Python programming with strong software engineering best practices, including clean code, code reviews, testing, and production-grade deployments.
• Proficient in software design patterns and development methodologies applicable to AI/ML projects.
• Experience with GitLab repositories, version control, and CI/CD pipelines.
• Hands-on experience with Google Cloud Platform (GCP) services and managing cloud-based AI workloads.
• Skilled in working with on-premises Linux-based GPU computing environments.
• Familiarity with containerization and orchestration technologies (Docker, Kubernetes) is a plus.
• Good understanding of supervised, unsupervised, and reinforcement learning algorithms and techniques.
• Practical experience with neural networks, including CNNs, RNNs, Transformers, and their application in ML solutions. (Nice to Have)
• Expertise in developing, deploying, and optimizing AI/ML models for performance, scalability, and cost-efficiency.
• Strong knowledge of Large Language Models (LLMs), Prompt Engineering, and Generative AI frameworks.
• Experience with Agentic AI frameworks such as ADK for building multi-agent systems.
• Ability to design and implement AI-driven decision-making and tool-using agents.
• Competency in SQL, data preprocessing, feature engineering, and building ETL pipelines.
• Skilled in exploratory data analysis (EDA), visualization, and result interpretation.
• Experience with distributed computing frameworks for large-scale data processing.

Nice to have:

• Familiarity with Knowledge Graphs and graph databases such as Neo4j.
• Basic understanding of data modeling, ontologies, and schema design principles.

• Build and develop Agentic AI- / GenAI- based solutions.
• Integrate AI models into production systems working closely with other engineering teams.
• Optimize models for performance, scalability and cost-effectiveness.
• Prepare, explore and analyze data using Python.
• Work with an on-premises, Linux-based GPU computing platforms and cloud-based instances especially Google Cloud Platform.
• Document technical approaches, model architectures and implementation details.
• Be a strong and transparent communicator able to work with customers to set goals, identify risks and prerequisites, report progress, present results and seek feedback.
• Collaborate with data science, POs and IT teams to define requirements into implementation.