Senior Multimodal ML Engineer: Vision & Audio, Relocation

Npv; Paris; Hybride; EUR 86 000 - 215 000; Plein temps

Avantages offerts par ce poste

Visa and relocation assistance

Equity

Résumé du poste

White Circle is seeking a Multimodal ML Engineer to join its AI Safety team, building the policy enforcement and optimization layer for AI systems. You will train and fine-tune large-scale multimodal models from scratch and from pretrained checkpoints, and design experiments and data pipelines to support robust development.

You will deploy end-to-end alignment pipelines (SFT, DPO, GRPO), optimize for production (quantization, distillation, streaming), and define evaluation metrics that truly

Qualifications

• 3+ years of experience training large-scale multimodal models.
• Strong PyTorch and distributed training experience (DeepSpeed, FSDP).
• Familiarity with multimodal architectures (LLaVA, Qwen-VL, InternVL, Audio Flamingo, Whisper, HuBERT, Conformer).
• Hands-on RLHF/alignment across modalities (GRPO, DPO, reward modeling).
• Experience with both audio and video sequence modeling and large-scale dataset curation for production inference.
• Relocation to Paris or London (hybrid) required.

Responsabilités

• Train and fine-tune large-scale multimodal models from scratch and from pretrained checkpoints.
• Design experiments, build multimodal data pipelines, and train MoE architectures.
• Build alignment pipelines (SFT, DPO, GRPO), optimize for production (quantization, distillation, streaming), and deploy end-to-end.
• Define evaluation metrics that actually matter for the product.

Connaissances

PyTorch

DeepSpeed

FSDP

Multimodal architectures

RLHF alignment

Audio/Video modeling

Production inference optimization

Outils

Distributed training tooling

GPU clusters

Description du poste

White Circle is seeking a Multimodal ML Engineer to join its AI Safety team, building the policy enforcement and optimization layer for AI systems. You will train and fine-tune large-scale multimodal models from scratch and from pretrained checkpoints, and design experiments and data pipelines to support robust development.

You will deploy end-to-end alignment pipelines (SFT, DPO, GRPO), optimize for production (quantization, distillation, streaming), and define evaluation metrics that truly