Founding Lead Machine Learning Engineer
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The role
Lead end-to-end ML product development, from data to deployment, shaping model architectures and training pipelines.
Experiment with frontier language models (LLaMA, Mistral, Qwen) and design scalable inference stacks (vLLM, TensorRT-LLM, DeepSpeed).
Own data systems for high-quality synthetic and real-world training data, with emphasis on alignment, safety, and guardrails.
Develop evaluation frameworks across performance, robustness, safety, and bias to drive product decisions.
Drive GPU-optimized deployment, latency reduction, and scalable policies for a global consumer AI product.
Shape early product direction and explore frontier techniques like retrieval-augmented training and mixture-of-experts.
Experiment with frontier language models (LLaMA, Mistral, Qwen) and design scalable inference stacks (vLLM, TensorRT-LLM, DeepSpeed).
Own data systems for high-quality synthetic and real-world training data, with emphasis on alignment, safety, and guardrails.
Develop evaluation frameworks across performance, robustness, safety, and bias to drive product decisions.
Drive GPU-optimized deployment, latency reduction, and scalable policies for a global consumer AI product.
Shape early product direction and explore frontier techniques like retrieval-augmented training and mixture-of-experts.
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