NLP & AI Research Engineer

For one of our clients, a product-based AI company in Germany, we are currently looking for an experienced AI/ML/ NLP Expert for 6 months B2B contract role.

Start date : ASAP

Our client is an innovative business where you will have the opportunity to work on cutting-edge NLP technology that goes beyond traditional text analytics. As a part of the team you will be helping global brands truly understand the why behind some of their customer motivations and decisions.

Working for our client, you will develop advanced ML solutions that turn complex data into meaningful business insights, for organisations across diverse industries.

You will play a key role in building and fine-tuning models that drive high-impact applications, from sentiment analysis and bot detection to fact-checking and topic discovery.

Your role:

• Train and fine-tune text classification and generation models for real-world NLP tasks.
• Apply advanced techniques such as few-shot learning, knowledge distillation, and adapters.
• Adapt large language models to specific domains and languages using further pretraining or multilingual techniques.
• Generate high-quality, domain-specific synthetic data to enhance performance on downstream tasks.
• Develop and implement traditional ML algorithms, with a focus on clustering embeddings and dimensionality reduction.
• Build scalable data pipelines and inference logic using Python, to be served via APIs.
• Design and run robust model evaluation scenarios for classification and generation tasks.
• Collaborate closely with engineering and research teams to translate experiments into production-ready tools.

Your Profile:

• Solid expertise in Natural Language Processing (NLP) and Artificial Intelligence (AI.)
• Strong experience with transformer-based models, including HuggingFace libraries (Transformers, Datasets, TRL, PEFT), Torch, and Sentence Transformers.
• Familiarity with synthetic data generation techniques.
• Proficiency in implementing ML workflows using frameworks like spaCy, scikit-learn, and others.
• Exposure to deployment tools such as Docker, Kubernetes, FastAPI, Triton, or VLLM (a plus.)
• Ability to write clean, efficient Python code for both batch analytics and real-time inference.
• Experience designing experiments for model evaluation and benchmarking.
• Familiarity with Azure cloud services (a plus.)
• Fluent in English (written and spoken.)

If you are ready to take the next step in your professional career and you are available immediately, please apply.