Founding Machine Learning Engineer
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Die Stelle
Shape the core ML stack end-to-end from data to deployment for a global consumer AI product.
Design end-to-end training pipelines and experiment with frontier models to define the architecture and model selection.
Build scalable inference systems (vLLM, TensorRT-LLM, DeepSpeed) and data platforms for high-quality synthetic and real-world data.
Develop alignment, safety, and guardrail strategies and design evaluation frameworks for performance, robustness, safety, and bias.
Own deployment optimization: GPU memory efficiency, latency reduction, and scaling policies in production.
Operate with a founder's mindset—ambition, ownership, and relentless iteration to ship high-impact AI experiences.
Design end-to-end training pipelines and experiment with frontier models to define the architecture and model selection.
Build scalable inference systems (vLLM, TensorRT-LLM, DeepSpeed) and data platforms for high-quality synthetic and real-world data.
Develop alignment, safety, and guardrail strategies and design evaluation frameworks for performance, robustness, safety, and bias.
Own deployment optimization: GPU memory efficiency, latency reduction, and scaling policies in production.
Operate with a founder's mindset—ambition, ownership, and relentless iteration to ship high-impact AI experiences.
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