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xAI

Finance Expert - Quantitative Trading

Posted Yesterday
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Remote
Hiring Remotely in USA
45-100 Hourly
Senior level
Easy Apply
Remote
Hiring Remotely in USA
45-100 Hourly
Senior level
The Quantitative Trader will enhance AI systems through expert input on quantitative trading strategies, market modeling, and data evaluations while collaborating with technical teams.
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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.

Quantitative Trader’s Role in Advancing xAI’s Mission

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.

Scope

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
Key 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 Qualifications
  • 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 & Other Expectations
  • This position is based fully remote.
  • If you are based in the US, please note we are unable to hire in the states of Wyoming and Illinois at this time.
  • We are unable to provide visa sponsorship.
  • Team members are expected to work from 9:00am - 5:30pm PST for the first two weeks of training and 9:00am - 5:30pm in their own timezone thereafter.
  • For those who will be working from a personal device, please note your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.
Compensation

$45/hour - $100/hour

The posted pay range is intended for U.S.-based candidates and depends on factors including relevant experience, skills, education, geographic location, and qualifications. For international candidates, our recruiting team can provide an estimated pay range for your location.

Benefits:

Hourly pay is just one part of our total rewards package at xAI. Specific benefits vary by country, depending on your country of residence you may have access to medical benefits. We do not offer benefits for part-time roles.

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

Top Skills

Bloomberg
Capital Iq
Crsp/Compustat
Factset
Python
PyTorch
R
Refinitiv
Sec Edgar
Taq
TensorFlow

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