Teams at White Circle

Build and maintain scalable ML infrastructure for LLM post-training, RL, evaluation, inference, and agentic workflows. Design data-control systems, optimize training and inference performance across networking, storage, and compute, and deliver tooling for experiments, evals, dashboards, reproducibility, and failure inspection. Collaborate with researchers and product to iterate models and infrastructure.

Train, fine-tune, and deploy large-scale multimodal models (vision, video, audio, speech). Build multimodal data pipelines, run experiments, optimize MoE and inference (quantization, distillation, low-latency), and develop multimodal alignment/RLHF pipelines. Define evaluation benchmarks and ship models to production.

Build and automate GTM systems to acquire and retain customers: own CRM, design GTM data model, create pipelines, deploy AI agents, build integrations and enrichment workflows, and iterate on outbound/inbound playbooks to generate qualified pipeline.