Sr. Research Engineer, ML for AGI - Multimodal LLMs
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La posizione
Lead the development of state-of-the-art multimodal LLMs from pre-training to post-training workflows.
Scale model training on massive GPU and AWS Trainium clusters, optimizing distributed training and parallelism.
Refine low-level training stack components (CUDA kernels, collectives, network I/O) for high efficiency.
Build, extend, and evaluate using leading frameworks (NeMo, Megatron Core, PyTorch, Jax, vLLM, TRT).
Collaborate across teams to prototype novel techniques, assess feasibility, and deliver robust AI systems.
Operate in a fast-moving Agile environment, shaping architecture and best practices for reliable GenAI products.
Scale model training on massive GPU and AWS Trainium clusters, optimizing distributed training and parallelism.
Refine low-level training stack components (CUDA kernels, collectives, network I/O) for high efficiency.
Build, extend, and evaluate using leading frameworks (NeMo, Megatron Core, PyTorch, Jax, vLLM, TRT).
Collaborate across teams to prototype novel techniques, assess feasibility, and deliver robust AI systems.
Operate in a fast-moving Agile environment, shaping architecture and best practices for reliable GenAI products.
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