Our client is a Barcelona-based fintech startup delivering systematic, risk-managed exposure to digital assets. Their mission is to make institutional-grade crypto investing accessible through robust quantitative strategies and optimized portfolio construction.About the OpportunityAre you passionate about building ML models that are live in the markets? Do you want to turn research into real-world quantitative strategies that manage millions? Then this role is for you.We’re looking for a Quantitative AI/ML Engineer to lead research, development, and deployment of advanced ML systems powering our algorithmic strategies. You’ll design predictive models, optimize real-time trading logic, and ensure performance and explainability, bridging financial data science, quantitative research, and MLOps. You’ll work closely with the CTO, Head of Quant Research, Quant Engineers, and software team to translate ideas into deployed code, while also owning our MLOps pipelines and research stack.Requirements:MSc or PhD in Machine Learning, Applied Mathematics, Physics, or Financial Engineering is highly preferred and will be considered a strong plus.Expert in Python, data science libraries (NumPy, pandas, scikit-learn), and ML frameworks (PyTorch, TensorFlow).Cloud computing experience (AWS preferred, or Azure).Strong grasp of time-series modeling and ML (ideally for financial data).Comfortable reading academic papers and turning theory into production-ready tools.Passion for research, speed, and solving hard problems with real-world impact.Knowledge of reinforcement learning, Bayesian optimization, or probabilistic models is a strong plus.Strong research skills, capacity to read and digest academic papers, and the ability to quickly apply new methods.Experience building and deploying ML models (versioning, retraining, monitoring).Skilled in feature engineering and integrating alternative data sources.Bonus: Knowledge of C++/Rust for performance-critical components.Pluses:Experience designing and deploying algorithmic trading strategies.Experience applying reinforcement learning or Bayesian optimization to financial use cases.Understanding or substantial interest in financial markets — preferably with exposure to crypto markets, DeFi, or trading systemsFamiliarity with on-chain data extraction and analysis (Web3/crypto).Prior work experience in a hedge fund, prop trading firm, or crypto trading desk.What’s in it for you?Founding team member opportunity — Be one of our first hires, with direct influence on their trading models from day one.High-impact projects —Your work will directly shape live strategies used by top-tier investors managing millions.Fast-track career growth in a high-performance environment where your impact is visible and rewarded, and where you scale into leadership roles as the company and tech expand.Meaningful equity package — Build this with them and share in the upside.Be part of a top-tier fintech startup — Backed by leading investors and advisors, building the future of digital asset investing.High ownership and autonomy — Lead, build, and ship — no layers, no bureaucracy.They’re committed to investing in your future—whether it’s funding courses, certifications, or other educational opportunities, we want you to continually grow and excel.Career ProgressionAs one of their first Quantitative Engineers, you’ll begin by owning core research and model development, evolve into Quant Lead, and later take on a Head of Quant Trading role as the team expands. You’ll help define their research agenda, shape the next generation of the company strategies, and mentor new team members as we scale their infrastructure and client base.CompensationThey believe in transparency and competitiveness:Base Salary Range: €38,000 - €52,000 gross annual + 10% bonusEquity Package: Meaningful equity package — share the upside as they grow from Pre-Seed to global scale.Total Compensation: Competitive and designed to grow as they scale, with compensation reviews twice per year.