ABOUT xAI

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.

ABOUT THE ROLE:

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 real-world reasoning.

Quantitative Traders provide labeling, annotation, evaluation, and expert reasoning services across text, voice, and video data modalities to support model training and evaluation. The role may include recording audio responses, participating in video-based tasks, or producing step-by-step quantitative reasoning traces — all of which are essential job functions required to fulfill xAI’s mission. All outputs are considered work-for-hire and owned by xAI.

RESPONSIBILITIES:

Use proprietary annotation and evaluation software to provide precise labels, rankings, critiques, and detailed solutions on assigned projects
Deliver consistently high-quality, curated data that meets strict technical and scientific standards
Collaborate with engineers and researchers to support the creation and iteration of new training tasks and evaluation benchmarks
Provide feedback that helps improve the usability, efficiency, and precision of annotation and data-collection tools
Select and solve complex problems from quantitative trading domains where you have deep expertise — examples include:

Factor model construction and signal combination
Market microstructure and order book dynamics
Statistical arbitrage and pairs/cointegration strategies
ML-driven alpha generation and feature engineering
Optimal execution algorithms and transaction cost modeling
Portfolio construction under constraints (risk, turnover, sector, etc.)
Risk modeling and stress-testing frameworks

Deliver rigorous model critiques, alternative solutions, mathematical derivations, and quantitative reasoning when evaluating AI outputs
Interpret, analyze, and execute tasks efficiently based on detailed (and sometimes evolving) instructions

BASIC QUALIFICATIONS:

Master’s or PhD in a strongly quantitative field:
Quantitative Finance, Financial Engineering, Financial Mathematics, Statistics, Applied Mathematics, Computer Science (with finance focus), Physics, Operations Research, Econometrics, or closely related discipline or equivalent professional experience as a quantitative researcher / systematic trader
Excellent written and verbal communication in professional English (both technical and explanatory styles)
Deep familiarity with financial data sources and platforms (Bloomberg, Refinitiv, FactSet, Capital IQ, SEC EDGAR, CRSP/Compustat, TAQ, earnings transcripts & call databases, alternative data providers, etc.)
Exceptional analytical reasoning, attention to detail, and ability to make sound judgments with incomplete information
Genuine passion for quantitative methods, systematic trading, machine learning in finance, and frontier AI technology

PREFERRED SKILLS AND EXPERIENCE:

Professional experience in quantitative trading, systematic strategies, or quant research at a hedge fund, prop trading firm, asset manager, or investment bank
Track record of publication(s) in refereed journals/conferences in finance, econometrics, machine learning, or related fields
Prior teaching, mentoring, or tutorial experience (university level or industry training)
Working proficiency in Python (pandas, NumPy, SciPy, scikit-learn, PyTorch/TensorFlow, statsmodels, polars, etc.) and/or R for financial modeling and data analysis
Familiarity with backtesting frameworks, vectorized computation, and handling large financial datasets
CFA, FRM, CQF, CAIA or similar professional designations
Experience with high-frequency data, execution algorithms, or market microstructure research
Previous work involving large language models, reinforcement learning, or AI evaluation pipelines (a strong plus)

LOCATION AND OTHER EXPECTATIONS:

Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit.
For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.
Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs.
For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time.
We are unable to provide visa sponsorship.
For those who will be working from a personal device, your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.

COMPENSATION AND BENEFITS:

US based candidates: $45/hour - $100/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.

Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process.

xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.