AI Jobs in Web3

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Job Position Company Posted Location Salary Tags

Binance

Taipei, Taiwan

Zap

Remote

$103k - $118k

Inmobi

Remote

Cere Network

Warsaw, Poland

Ivy Creations

United States

$45k - $52k

Binance

Taipei, Taiwan

Gambit Markets

Remote

$20k - $40k

Tether

London, United Kingdom

$115k - $117k

Binance

Canada

ELYON - Infinite Blockchain | First True AGI | Inventor of Scrolls/PlanckScale in AI and Blockchain

United States

$94k - $150k

Circle

U.S. - California Ηνωμένες Πολιτείες της Αμερικής

$172k - $212k

Improbable

London, United Kingdom

$90k - $118k

Iftother

Remote

$60k - $90k

Tether

TI Lugano CH

$115k - $117k

Crypto.com

Hong Kong, Hong Kong

$118k - $150k

Binance
Taiwan, Taipei
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Data Scientist, Quantitative Trading (NLU/NLP)

Asia / Taiwan, Taipei / Thailand, Bangkok / Australia, Brisbane / Australia, Melbourne / Australia, Sydney
Engineering – Data Science/AI /
Full-time: Remote /
Remote

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Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 250 million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

About the Role
This role sits at the intersection of quantitative finance, machine learning, and natural-language understanding. You’ll leverage NLU techniques—like sentiment and intent analysis—to mine news and social media for trading signals, build and mathematically refine predictive models, and rigorously backtest and optimize your strategies to drive data-driven investment decisions.

Responsibilities:

    • Research and develop quantitative trading strategies using NLU methods—sentiment analysis, intent recognition, named-entity extraction—on financial news, social media, and other text sources
    • Design and build machine-learning models to uncover predictive trading signals and perform exploratory data analysis on large, complex datasets
    • Apply mathematical techniques (probability, statistics, time-series analysis) to refine and strengthen trading models
    • Rigorously backtest strategies against historical data and iteratively optimize models to boost performance and curb risk

Requirements:

    • Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Financial Engineering or a related discipline
    • Solid grasp of NLU techniques, including sentiment analysis, intent recognition, and named-entity recognition
    • Proficiency in Python or R, with hands-on experience in NLP libraries (SpaCy, NLTK, Transformers)
    • Strong mathematical foundation—probability, statistics, linear algebra, time-series analysis—and familiarity with ML frameworks (Scikit-learn, TensorFlow, PyTorch)
    • Excellent analytical and problem-solving abilities, with strong communication and teamwork skills
    • Bilingual English/Mandarin is required to be able to coordinate with overseas partners and stakeholders.
Why Binance
• Shape the future with the world’s leading blockchain ecosystem
• Collaborate with world-class talent in a user-centric global organization with a flat structure
• Tackle unique, fast-paced projects with autonomy in an innovative environment
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning
• Competitive salary and company benefits
• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)

Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.
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What an AI Developer does?

An AI developer is someone who creates and builds artificial intelligence systems

Their responsibilities may include designing and implementing algorithms, creating and training machine learning models, and deploying AI systems to solve practical problems

Additionally, they may be responsible for maintaining and improving existing AI systems, as well as collaborating with other teams or individuals to integrate AI technology into larger systems.