MLE / MLOps

White Circle seeks an MLE / MLOps to optimize inference stack, bridging Research and Product for fast, production-ready models.

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 and fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model.

## What you'll do

• •Own inference infrastructure end-to-end: optimize latency, throughput, and cost across our model fleet.
• •Build and scale model serving with TensorZero, vLLM/SGlang/TRT, and Kubernetes.
• •Design and maintain vector search pipelines with Vector storages.
• •Turn research into product: grab experimental models from the research team, figure out what's production-ready, and ship it.

## Conditions

• •Salary of $100,000 to $150,000 + equity.
• •20 days of paid vacation.
• •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.

• •3+ years shipping high performance ML systems in production.
• •Deep hands-on experience with inference optimization.
• •Comfortable across the stack: from CUDA kernels to Kubernetes manifests to Grafana dashboards.
• •Experience with Rust, custom Triton kernels, benchmarks is a plus.