Principal Machine Learning Engineer, AI Platform (Foundation Model Post-Training)
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La posizione
You will lead the post-training phase of foundation models, aligning models with business intent and domain requirements.
Design and implement scalable, distributed pipelines for SFT, RLHF, and instruction tuning on multi-node GPU clusters.
Oversee data strategy, annotation workflows, and automated data filtering to curate high-quality instruction data.
Build comprehensive evaluation suites, including automated benchmarks and human-in-the-loop protocols, to assess performance and safety.
Optimize training efficiency with quantization, distillation, LoRA/Q-LoRA, and memory optimizations.
Provide technical leadership and mentorship across engineering, research, and product teams, translating research into production-ready systems.
Design and implement scalable, distributed pipelines for SFT, RLHF, and instruction tuning on multi-node GPU clusters.
Oversee data strategy, annotation workflows, and automated data filtering to curate high-quality instruction data.
Build comprehensive evaluation suites, including automated benchmarks and human-in-the-loop protocols, to assess performance and safety.
Optimize training efficiency with quantization, distillation, LoRA/Q-LoRA, and memory optimizations.
Provide technical leadership and mentorship across engineering, research, and product teams, translating research into production-ready systems.
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