Sr. Research Engineer, Machine Learning, AGI Foundations
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The role
Lead the design and implementation of multimodal large-language models (LLMs) and foundational AI capabilities.
Own pre-training and post-training workflows, optimizing training efficiency on massive GPU and AWS Trainium clusters.
Advance algorithms and modeling techniques, prototype new approaches, and evaluate feasibility.
Fine-tune system architecture and low-level training stack (CUDA kernels, collectives, IO) for high performance.
Leverage industry frameworks (NeMo, Megatron Core, PyTorch, Jax, vLLM, TRT) and build scalable pipelines.
Collaborate effectively in a self-organizing Agile environment, delivering impactful features in a fast-growing setting.
Own pre-training and post-training workflows, optimizing training efficiency on massive GPU and AWS Trainium clusters.
Advance algorithms and modeling techniques, prototype new approaches, and evaluate feasibility.
Fine-tune system architecture and low-level training stack (CUDA kernels, collectives, IO) for high performance.
Leverage industry frameworks (NeMo, Megatron Core, PyTorch, Jax, vLLM, TRT) and build scalable pipelines.
Collaborate effectively in a self-organizing Agile environment, delivering impactful features in a fast-growing setting.
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