Senior AI/ML Engineer or Postdoctoral Researcher - LLM Infrastructure (m/f/d)

About

TIB, part of the Leibniz Research Association with around 600 employees, is one of the largest technical information centres in Germany. It acts as the Leibniz Information Centre for Science and Technology, conducts cutting edge research, and offers library services for Leibniz University Hannover. As the German National Library of Science and Technology, TIB ensures high-quality information and literature supply for research in science and industry. With the Open Research Knowledge Graph (ORKG), TIB aims to revolutionize scientific knowledge exchange in the digital age.

Your role

We are seeking a Senior AI / ML Engineer interested in building, optimizing, and operating general-purpose AI assistants at scale within the European Open Science Cloud (EOSC) ecosystem. The role focuses on scalable training and inference pipelines, token-efficiency and model selection strategies, distributed ML systems in production, and evaluation of open models. It includes optimizing latency, cost and performance trade-offs, supporting parameter-efficient adaptation workflows, and ensuring reliable integration with orchestration layers in EOSC service environments.

Your responsibilities

• Designing and developing inference infrastructure in cloud environments, with continuous optimization for latency, throughput and cost efficiency
• Benchmarking models against task-specific and general-purpose evaluation criteria and deriving data-driven recommendations on model-task fit
• Applying quantization, distillation, parameter-efficient fine-tuning and other optimization techniques to improve efficiency, performance and cost-effectiveness
• Building an orchestration layer that integrates seamlessly with the broader agent framework and supports emerging AI protocols such as MCP, A2A and ACP
• Embedding observability from the outset using tools such as OpenTelemetry and Grafana to make model performance, cost and reliability transparent, measurable and actionable

Your profile

• Completed scientific university degree (Master’s degree or equivalent) in computer science, software engineering, artificial intelligence, data science or a related field
• Proven experience with LLM inference optimization in cloud environments
• Practical experience with fine-tuning, quantization, parameter-efficient fine-tuning (PEFT) and deployment of large language models in production or production-like settings
• Experience with model profiling, benchmarking and establishing performance baselines
• Experience in designing, developing or operating scalable training and inference pipelines within distributed AI/ML systems
• Knowledge of multi-agent systems, agentic workflows or orchestration frameworks, such as LangGraph or AutoGen
• Experience working with open-source LLMs, such as Llama or Mistral
• Very good programming skills in Python and experience in developing reproducible code, e.g. using PyTorch or comparable frameworks
• Good knowledge of cloud-native technologies, in particular Docker and Kubernetes
• Very good written and spoken English skills

Desirable additions to your profile

• Completed PhD in a relevant field
• Experience with agentic design patterns, such as reflection, ranking, exploration/discovery or human-in-the-loop feedback loops
• Experience handling scientific datasets and applying FAIR principles to data, model outputs or research workflows
• Strong written communication skills and experience in interdisciplinary collaboration, including contributions to scientific publications
• Familiarity with the Rust programming language

What we offer

• A job in the public service oriented towards the common good based on the collective agreement for the public service of the German states (TV-L) with salary in pay scale group 13 TV-L
• Flexible workplace in terms of time and space with offers to reconcile work and family life, including mobile and remote work options and flexible working time models (flexitime)
• Special annual payment at the end of the year and 30 days of vacation per year with a five-day working week plus additional days off on Christmas Eve and New Year's Eve
• Modern workplace in a central location of Hannover with a collegial, attractive and versatile working environment
• Wide range of internal and external further education and training measures, workplace health promotion and a supplementary pension scheme for the public sector (VBL)
• Employee discount in the canteens of the Studentenwerk Hannover and discounted offers of the University Sports Hannover
• Independent and future-oriented activities offering variety and room for personal development
• Funding for necessary equipment, conference and research visit travel
• Work in the context of national, European or international research and innovation projects
• A portfolio of technology components to build on, including ORKG, OpenResearch.org, TIB AV-Portal, DBpedia.org and others

Additional information

• The position is initially limited to three years with envisioned extension
• Regular weekly working hours are 39.8 hours (full-time); part-time work is generally suitable
• The position is generally expected to be carried out on site in Hanover with mobile work possible to a certain extent, subject to operational requirements
• Equal opportunity employer promoting equal career opportunities and encouraging qualified women to apply
• Preferential consideration for severely disabled candidates or those with equivalent status
• Application deadline June 14, 2026
• Contact: Prof. Dr. Sahar Vahdati, Sahar.Vahdati@tib.eu
• Application via website or email with subject 16/2026
• Foreign university degrees require a Statement of Comparability from the Central Office for Foreign Education (ZAB)