We’re a cutting-edge quant trading firm pushing the frontier of crypto markets using data-driven strategies, advanced AI models, and custom-built infrastructure. Our team consists of elite traders, AI researchers, and engineers on a mission to conquer inefficiencies in digital asset markets through speed, intelligence, and automation.Job DescriptionWhat You'll DoAs a Crypto Quant Researcher – Applied AI Intern, you’ll:Research, design, and backtest systematic strategies across centralized and decentralized crypto marketsApply AI/ML techniques (LLMs, transformers, reinforcement learning, etc.) to generate, evaluate, and evolve trading featuresBuild real-time models using on-chain data, sentiment feeds, and market microstructure signalsAutomate strategy generation pipelines using multi-agent systems or prompt engineeringCollaborate with traders and engineers to improve alpha detection, risk metrics, and execution logicContribute to the research wiki, idea logs, and internal factor librariesWhat We’re Looking ForStrong background in quantitative research, AI/ML, or statisticsExperience with Python, Pandas, Numpy, and at least one ML framework (PyTorch, TensorFlow, scikit-learn)Familiarity with crypto markets (DEX/CEX mechanics, DeFi protocols, or trading strategies)Understanding of backtesting, alpha modeling, or reinforcement learning is a plusBonus: Knowledge of LLMs, prompt tuning, or agent-based systemsWhy Join Us?Work at the intersection of crypto, AI, and quantitative financeGain hands-on experience building models and strategies used in live tradingMentorship from industry veterans and hands-on trainingHigh-impact role with real responsibilities from day onePotential for full-time conversion for top performersTo Apply: Send your CV, GitHub (if any), and a short paragraph on why you're interested in crypto + AI to [your email address or application link].Early applicants get priority. Only shortlisted candidates will be contacted.Application InstructionsPlease apply for this position by submitting your text CV using InternSG. Kindly note that only shortlisted candidates will be notified.