Job description:
Duration: Feb / March
- 12 months + +
Capacity: 80-100%
Location: Remote
1\. Role description
The Senior Machine Learning / NLP Engineer designed, developed, trained and operated advanced Chinese learning
- and natural language processing solutions in productive environments. The focus is on data-driven, scalable KI systems, especially in the context of word processing, large language models (LLMs) and Generative AI.
2\. Tasks and services
2.1 Conception & Architecture
- Analysis of technical requirements and translation into ML- / NLP solution designs
- Design of end-to-end architectures (data pipeline, training, inference, monitoring)
- Selection of suitable models, frameworks and infrastructure
2.2 Development & Modeling
- Development and training of ML
- and NLP models, including:
- text classification, information extraction, NER
- Semantic Search, RAG architectures
- Conversational AI / Chatbots
- LLM Fine tuning (e.g. PEFT, LoRA)
- Implementation in Python using common ML- / DL- frameworks
2.3 Integration & Productivity
- Integration of the models into existing applications and IT landscapes
- Development of information services (APIs, batch, streaming)
- Ensuring performance, scalability and stability
- Support for MLOps (CI / CD, model version, monitoring)
2.4 Quality, governance & security
- Assessment of model quality, bias, robustness and traceability
- Documentation of models, training data and decisions
- Compliance with data protection, security
- and compliance requirements
2.5 Consulting & knowledge transfer
- Technical advice of stakeholders (IT, departments, management)
- Support of teams in architecture
- and technology decisions
- Knowledge transfer and enablement of internal teams
3\. Technical qualification (minimum requirements)
- Multi-year practical experience (type.? 5 years) in the area of:
- Machine Learning
- Natural Language Processing
- Very good knowledge in:
- Python
- ML- / DL- Framework (e.g. PyTorch, TensorFlow)
- NLP libraries and LLM ecosystems
- Experience with productive KI systems (not only research / prototypes)
- Sound understanding of statistics, data structures and algorithms
4\. Additional qualifications (relevant to the project)
- experience with:
- Cloud platforms (AWS, Azure, GCP or sovereign cloud environments)
- Containerisation (docker, copper net)
- Vector databases and search systems
- knowledge in:
- GenAA architectures
- Responsible AI / AI governance
- experience in regulated or safety-critical environments
5\. Working & Soft Skills
- Own, structured and result-oriented work
- Ability to communicate complex technical content
- High problem-solving competence
- Experience in interdisciplinary project teams