This is a start up-style role with broad ownership across AI development, data collection, robot integration, testing, failure analysis, and continuous performance improvement. The ideal candidate is comfortable working across disciplines and taking ideas from early experimentation through to real-robot deployment.
We are looking for a hands-on Embodied AI Engineer with experience in robot learning to develop, fine-tune, deploy, and validate intelligent behaviors on physical humanoid robots.
Model Deployment & Fusion. Bridge the gap between AI research and production. Optimize deep learning models for efficient inference and ensure seamless integration of compression algorithms into deployment frameworks (e.g., vLLM).
Reporting directly to the AI Architect, the Staff AI Systems Engineer will serve as a key technical partner in translating AI product requirements and architectural vision into deployable AI solutions.
Build AI-powered features into business applications — such as integrating LLM APIs, embedding AI assistants, or adding intelligent automation — to enhance existing Java, .NET Core, and TypeScript applications.
Architect real-time and near-real-time data feeds for AI agents that require current information: market data integration, news and research feed ingestion, portfolio event streaming, and alert-triggering data pipelines — with latency and freshness SLAs defined and enforced.
This internship provides exposure to the full development pipeline, including data collection, model training, robot integration, simulation, real-world testing, and failure analysis.