Timothée Lacroix

Co-Founder & Chief Technology Officer

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ABOUT

Co-founder & CTO at Mistral AI and former research engineer at Meta AI. Architect of the distributed training clusters and high-performance inference pipelines powering Mistral's open and commercial models, specializing in sharded tensor parallelism and FP8 cluster optimization.

Areas of focus

Professional niches

THE WORK BEHIND THE PROFILE

Proof of Work

implementationChecked Sep 22, 2026

mistral-src: Reference Implementation and MoE Inference Engine

Built the official open-source reference codebase for Mistral 7B and Mixtral 8x7B, implementing sliding window attention (SWA), dynamic chunking, and Megatron-style tensor parallel execution for multi-GPU serving.

Scope & limitations

Sliding window attention truncates attention cache for earlier tokens outside the local window unless global tokens are designated.

Context: Sliding window attention (W=4096), grouped-query attention (GQA), PyTorch.

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implementationChecked Sep 22, 2026

Large-Scale Distributed Pre-Training and Sharded Tensor Parallelism

Architected the cluster infrastructure utilizing Megatron-LM and custom NCCL collective communication topologies that pre-trained the Mixtral family across thousands of H100 GPUs with near-linear scaling efficiency.

Scope & limitations

Inter-node all-to-all communications in large MoE routing can bottleneck throughput on non-InfiniBand cloud interconnects.

Context: H100 NVLink clusters, InfiniBand HDR/NDR fabric, FP8 mixed precision.

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