Founding Machine Learning Engineer
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Die Stelle
Own end-to-end training pipelines—from data collection to inference—delivering real-world AI experiences.
Design and adapt transformer architectures, exploring frontier models and open-source options to match product needs.
Fine-tune models with state-of-the-art methods (LoRA, QLoRA, SFT, DPO, distillation) while ensuring alignment and safety.
Architect scalable inference systems using vLLM, TensorRT-LLM, and DeepSpeed, with GPU optimization and latency goals.
Build data systems for high-quality synthetic and real-world training data and robust evaluation frameworks.
Shape early product direction, experiment with new use cases, and pioneer advanced techniques like retrieval augmentation and multimodal capabilities.
Design and adapt transformer architectures, exploring frontier models and open-source options to match product needs.
Fine-tune models with state-of-the-art methods (LoRA, QLoRA, SFT, DPO, distillation) while ensuring alignment and safety.
Architect scalable inference systems using vLLM, TensorRT-LLM, and DeepSpeed, with GPU optimization and latency goals.
Build data systems for high-quality synthetic and real-world training data and robust evaluation frameworks.
Shape early product direction, experiment with new use cases, and pioneer advanced techniques like retrieval augmentation and multimodal capabilities.
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