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About the Role **
We’re looking for a
Generative AI Data Scientist
to design, train, and optimize AI models that power next-generation intelligent systems. You’ll work on projects involving large language models (LLMs), NLP, and multimodal data pipelines — helping turn research into production-grade products.
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Responsibilities **
Develop and fine-tune generative AI models (LLMs, diffusion, transformer-based architectures).
Build and manage data pipelines for model training, evaluation, and continuous learning.
Design prompt engineering and retrieval-augmented generation (RAG) frameworks.
Collaborate with engineers and product teams to deploy scalable inference APIs.
Evaluate model performance, bias, and data quality; implement monitoring systems.
Contribute to model interpretability, safety, and responsible AI practices.
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Qualifications **
MS or PhD in Computer Science, Machine Learning, Statistics, or related field.
3+ years of experience in ML/AI, with exposure to generative or transformer-based models.
Strong Python skills (PyTorch, TensorFlow, Hugging Face, LangChain, etc.).
Experience with vector databases, RAG, and fine-tuning open-weight models (e.g., Llama, Mistral).
Familiarity with cloud ML environments (AWS Sagemaker, GCP Vertex, or Azure ML).
Excellent problem-solving and communication skills.
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Nice to Have **
Experience deploying AI systems in production.
Knowledge of multimodal (text, image, audio) model training.
Contributions to open-source AI projects or published research.
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What We Offer **
Competitive compensation
Flexible work environment.
Opportunity to work on frontier AI systems with real-world impact.
Sprachkenntnisse
- English
Hinweis für Nutzer
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