Founding Lead Machine Learning Engineer
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Die Stelle
Lead the end-to-end machine learning stack for a new global consumer AI product, from data to deployment.
Define model selection, training strategies, and long-term architecture; shape decisions that define the product's capabilities.
Design and operate end-to-end training pipelines: data collection, preprocessing, training, evaluation, and inference.
Experiment with frontier models (LLaMA, Mistral, Qwen, Claude-compatible) and develop novel approaches where needed.
Build robust alignment, safety, and guardrail strategies, and design evaluation frameworks for performance, robustness, safety, and bias.
Own deployment and optimization: GPU utilization, latency reduction, scalable policies, and ongoing product direction.
Define model selection, training strategies, and long-term architecture; shape decisions that define the product's capabilities.
Design and operate end-to-end training pipelines: data collection, preprocessing, training, evaluation, and inference.
Experiment with frontier models (LLaMA, Mistral, Qwen, Claude-compatible) and develop novel approaches where needed.
Build robust alignment, safety, and guardrail strategies, and design evaluation frameworks for performance, robustness, safety, and bias.
Own deployment and optimization: GPU utilization, latency reduction, scalable policies, and ongoing product direction.
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