xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.
As a Quantitative Trader, you will play a key role in improving xAI's advanced AI systems by delivering high-quality annotations, evaluations, and expert input using specialized labeling tools. You will collaborate closely with our technical teams to support the development and refinement of new AI capabilities, with a particular emphasis on quantitative trading domains. Your expertise will help select and solve challenging problems in systematic and quantitative strategies — including statistical arbitrage, factor investing, market microstructure modeling, high-frequency / execution algorithms, risk premia harvesting, machine learning-based alpha generation, and portfolio optimization under realistic constraints. This role requires strong analytical thinking, rapid adaptation to evolving guidelines, and the ability to provide rigorous, technically sound critiques and solutions in a fast-moving environment.
As a Quantitative Trader, you will directly contribute to xAI's mission by helping train and refine our frontier AI models. You will teach the models how quantitative traders reason, model markets, evaluate signals, manage risk, and interact with complex financial data and systems. This involves providing high-quality data in various formats (text, voice, video), writing detailed annotations, critiquing model outputs, recording audio explanations, and occasionally participating in structured video sessions. We are looking for individuals who are enthusiastic about these data-generation activities, as they form a core part of advancing xAI’s goals in scientific discovery and