Multimodal ML Engineer
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We're looking for a Multimodal ML Engineer to join White Circle, an AI Safety company building the policy enforcement and optimization layer for AI systems. Backed by $11M from senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, and DeepMind, White Circle processes 100M+ API calls monthly and runs its own LLMs in production.
You will
- Train and fine-tune large-scale multimodal models (vision-language, audio, speech, video) 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.
Requirements
- 3+ years training large-scale multimodal models.
- Strong PyTorch and distributed training experience (DeepSpeed, FSDP).
- Deep familiarity with multimodal architectures – LLaVA, Qwen-VL, InternVL, Audio Flamingo, Whisper, HuBERT, Conformer or similar.
- Hands-on RLHF/alignment across modalities (GRPO, DPO, reward modeling).
- Both audio and video experience required – sequence modeling for each, plus large-scale dataset curation and production inference optimization.
- Relocation to Paris or London (hybrid) required.
Bonus
- Audio signal processing fundamentals – spectrograms, mel features, noise reduction.
- MoE architecture experience.
We offer
- $100k–$250k/year salary + equity; higher figures can be negotiated.
- Official employment, visa and relocation help.
Compensation: $100K – $250K Higher figures and equity are negotiable
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