Quantitative AI / ML Engineer @ Quantitative Hedge Fund

Location: Remote / Hybrid
Hours: 16 - 32 hours/week
Salary: 18 - 20 EUR/hour

Do you want to work on live machine-learning driven trading systems in one of the most dynamic markets in the world? For an AI-driven quantitative hedge fund focused on cryptocurrency markets, we are looking for a Quantitative AI / ML Engineer who can help further develop, optimize, and professionalize a production-grade trading environment.

You will work on end-to-end quantitative trading systems, from research and modeling to deployment and live performance monitoring. This is a strong opportunity for someone who enjoys combining machine learning, software engineering, quantitative research, and market intuition in a real-world trading setting.

About the Company

Our client is building an AI-driven quantitative hedge fund focused on cryptocurrency markets. The company develops and runs machine-learning based trading strategies with a strong emphasis on robust backtesting, risk management, and scalable infrastructure.

The current production stack includes:

• Python
• Docker for containerized ML and trading pipelines
• OVH Cloud for compute and deployment
• Binance as execution venue

The goal is to further deepen and optimize this platform towards an institutional-grade trading setup.

Who Are We Looking For?

We are looking for applicants with a strong analytical mindset and a genuine interest in quantitative trading, machine learning, and crypto markets. This role is especially suitable for candidates who enjoy working independently, testing hypotheses, improving models, and translating research into live trading performance.

Role Description

As a Quantitative AI / ML Engineer, you will work across the full trading stack. Your responsibilities include:

• Further developing ML-driven trading strategies for Buy / Hold / Sell classification
• Designing and improving feature engineering, including technical, statistical, and regime-based features
• Training, validating, and comparing neural networks and other machine-learning models
• Improving labeling, backtesting, and walk-forward validation
• Integrating models into the live trading environment
• Optimizing live performance, stability, and risk control
• Maintaining and extending the Docker and cloud infrastructure
• Identifying and reducing overfitting, data leakage, and alpha decay

In this role, you will work directly on live markets in a continuous cycle of research → code → deployment → performance evaluation.

Must-haves

• Strong Python skills for both research and production-quality development
• Experience with machine learning on time-series data
• Understanding of backtesting, lookahead bias, and data leakage
• Affinity with crypto or other volatile financial markets
• Experience with Docker and Linux
• Analytical, research-driven, and problem-solving mindset

Nice-to-haves

• Experience with algorithmic trading or quantitative research
• Knowledge of risk management and position sizing
• Cloud experience such as OVH, AWS, or GCP
• Experience with neural networks or sequence models
• Familiarity with APIs and live execution environments such as Binance API

What We Offer

• A challenging part-time contract role in a highly innovative quantitative trading environment
• Direct exposure to live trading systems and real market behavior
• The opportunity to work on production-grade ML infrastructure
• Freedom to contribute across research, engineering, deployment, and optimization
• A technically ambitious environment where your work can have direct measurable impact
• Collaboration with a team focused on building institutional-level quantitative systems
• Salary: 18 – 20 EUR/hour (15 – 17 EUR/hour base salary + 8.3% holiday allowance + 8% holiday hours paid out upon request)

Interested?

Does this vacancy sound interesting to you? Then click the 'Apply Now' button now!

In the first year, you will be employed by CodeHive, and the company will hire you as a flexible professional. This means you will truly become part of both the CodeHive team and the company’s team. Through CodeHive, you can benefit from events, meetups, and courses to strengthen your professional skills and expand your network. After 1 or 2 years, you may have the opportunity to join the company directly, provided they also see this as a strong match. In this way, you can effectively explore your career opportunities while studying and gain clarity about your path after graduation.