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 Traders provide labeling, annotation, evaluation, and expert reasoning services across text, voice, and video data modalities to support model training and evaluation.

Requirements

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

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.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

quantitative tradingstatistical arbitragefactor investingmarket microstructure modelinghigh-frequency algorithmsrisk premia harvestingmachine learningportfolio optimizationPythonR

Soft Skills

analytical thinkingattention to detailsound judgmentwritten communicationverbal communicationcollaborationadaptabilityexpert reasoning

Certifications

CFAFRMCQFCAIA