We are working with an Amsterdam-based algorithmic trading firm that specializes in market making and arbitrage strategies across a wide range of digital assets and exchanges. Founded in 2021, they have developed a fully automated, ultra-low-latency trading infrastructure which executes thousands of trades daily across hundreds of order books. Having secured a leading position on multiple exchanges, they are now scaling rapidly: expanding to new venues, growing assets under management, and advancing the intelligence of their trading systems.

Our client’s next phase of growth focuses on maturing their strategies—making them smarter, more adaptive, and increasingly data-driven.

Your opportunity

This is a unique chance to join a fast-moving, entrepreneurial trading firm with a proven foundation and significant upside potential. You’ll be part of a small, high-performing team shaping the next generation of their algorithmic trading strategies.

In this role, you’ll have the opportunity to enhance and evolve trading models through quantitative research, machine learning, and large-scale data analysis. You’ll explore new opportunities, design and backtest data-driven strategies, and see your research directly impact trading performance in production environments.

Responsibilities

• Conduct quantitative and machine learning research to improve and expand existing trading strategies.
• Analyze large-scale, high-frequency market data to uncover inefficiencies and predictive patterns.
• Design and implement backtesting frameworks to validate and refine strategy ideas.
• Collaborate closely with engineers to deploy strategies in production.
• Continuously monitor, optimize, and fine-tune live strategies to ensure consistent performance.

Profile

• 2+ years of experience in a Machine Learning Engineer/Researcher role.
• Degree (BSc/MSc/PhD) in Math, Physics, Computer Science, Econometrics, Operations Research, or another quantitative field.
• Proficiency in Python and comfort working with large datasets, SQL, and data pipelines.
• Experience with machine learning, statistical modeling, or feature engineering for time-series or trading data is a strong plus.
• Ability to work autonomously, from idea to implementation, within a lean, collaborative team.
• Curiosity and genuine enthusiasm for trading and digital assets.
• Familiarity with Rust is a bonus.

What they offer

• Collaborative, high-energy work environment.
• Opportunity to become a key contributor at an early-stage trading firm with strong momentum.
• Competitive base salary + performance-based bonus scheme.
• Flexible hybrid setup (up to 2 days remote per week).
• Trendy East Amsterdam office with espresso bar and free lunch.
• 28 paid holidays and 1st Class train subscription for your commute.
• Visa sponsorship if needed.
• Top-tier equipment: MacBook Pro (14/16”) + headset of choice.
• Regular team events, drinks, and attendance at leading industry conferences.