AI Engineer (Vision)

About the role

White Circle is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies - simple natural-language rules that define what an AI model should and shouldn't do. We automatically test, enforce, and continuously improve these policies at scale. We've raised $11M from top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others We process over one hundred million API calls every month We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model We're a small, highly focused team. If you want to work deeply on hard problems, see your work ship to production quickly, and influence how AI safety is actually built - you're the one we need. You will: Train vision-language models from scratch and fine-tune existing architectures for image understanding Extend VLM capabilities to video: design temporal modeling approaches, handle long-context efficiently Design evaluation benchmarks that matter: visual QA, spatial reasoning, video comprehension Curate and maintain multimodal datasets - including synthetic data generation pipelines Train and optimize MoE architectures for efficient multimodal inference Deploy models to production: quantization, batching strategies, latency optimization You'll fit right in if you: 3+ years training and fine-tuning vision-language models (LLaVA, Qwen-VL, InternVL, or similar) Deep experience with multimodal architectures - you understand how vision encoders, projectors, and LLMs fit together Hands-on with RLHF/alignment for multimodal: GRPO, DPO, reward modeling - not just for text Experience with video understanding: temporal modeling, long-context processing, efficient attention mechanisms Track record shipping VLMs to production: you've optimized inference, not just reported benchmark scores Comfortable with large-scale dataset curation: image-text pairs, video-instruction data, synthetic data generation Familiar with MoE architectures and their tradeoffs for multimodal workloads Strong PyTorch skills, experience with distributed training (DeepSpeed, FSDP) Why White Circle Salary of $100,000 to $250,000 + equity Paid time off in line with your local regulations, no matter where you work from Work from Paris (hybrid) + relocation package Best medical insurance in France All the hardware, tools, and services you need Covered subscriptions for AI agents and IDEs Team off-sites twice a year: we've recently been to the Alps and to Saint-Tropez How we hire Intro call with one of our colleagues Сomplete the take-home assignment Show your best during the technical interview Final call with our CEO and CTO Please submit your application in English - it's our company language so you'll be speaking lots of it if you join

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TLDR: You'll train and fine-tune vision-language models, extend them to video, build alignment pipelines (GRPO, DPO, reward modeling), develop evaluation benchmarks, optimize inference for production, and work with MoE architectures.

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