Founding Lead Machine Learning Engineer
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Die Stelle
Own the end-to-end ML stack for a new global consumer AI product, from model selection and training to deployment and optimization.
Design and experiment with frontier models (LLaMA, Mistral, Qwen, Claude-compatible architectures) and novel architectures.
Lead fine-tuning strategies (LoRA/QLoRA, SFT, DPO, distillation) and GPU-optimized training workflows.
Architect scalable inference systems (vLLM, TensorRT-LLM, DeepSpeed) and data pipelines for high-quality synthetic and real-world data.
Develop alignment, safety, guardrails, and evaluation frameworks across performance, robustness, and bias; own latency and scalability.
Shape early product direction, exploring retrieval-augmented training, mixture-of-experts, multi-agent orchestration, and multimodal capabilities with an ownership-driven, founder mindset.
Design and experiment with frontier models (LLaMA, Mistral, Qwen, Claude-compatible architectures) and novel architectures.
Lead fine-tuning strategies (LoRA/QLoRA, SFT, DPO, distillation) and GPU-optimized training workflows.
Architect scalable inference systems (vLLM, TensorRT-LLM, DeepSpeed) and data pipelines for high-quality synthetic and real-world data.
Develop alignment, safety, guardrails, and evaluation frameworks across performance, robustness, and bias; own latency and scalability.
Shape early product direction, exploring retrieval-augmented training, mixture-of-experts, multi-agent orchestration, and multimodal capabilities with an ownership-driven, founder mindset.
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