Machine Learning / AI Engineer

Machine Learning / AI Engineer

About the Role

At Da Vinci Trading, we’re not just building trading systems, we’re building the future of intelligence in the markets. Our teams of researchers, quants, engineers and traders collaborate to push the boundaries of what's possible. If you’re passionate about machine learning, statistical modelling, and want your work to directly impact performance in real‑world financial markets, you’ll feel right at home here.

Responsibilities:

• Develop, test, and deploy novel ML/AI models for prediction, signal generation, and anomaly detection.
• Work closely with the Quant Research and Trading Intelligence teams to translate insights into live strategies.
• Explore state‑of‑the‑art techniques (e.g., deep learning, reinforcement learning, graph neural networks) and rigorously evaluate their applicability in financial domains.
• Analyze large, noisy, high‑frequency data streams; performing advanced feature engineering, data cleaning, and bias detection.
• Collaborate with our systems and infrastructure engineers to ensure models are productionised efficiently and reliably.
• Own the full lifecycle of your models, including performance monitoring, backtesting, risk assessment, and ensuring robustness.

Requirements:

• A strong academic background (MSc, PhD or equivalent) in Machine Learning, AI, Statistics, Computer Science, Mathematics, or a related field.
• Hands‑on experience building and deploying ML/AI models, especially for time‑series forecasting or anomaly detection.
• Proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow, JAX, scikit‑learn).
• Solid programming and software development skills, with experience in a production environment.
• Experience with core data and infrastructure tools like Docker, S3/MinIO, and PostgreSQL/OLAP databases.
• A deep, intuitive understanding of topics like overfitting, generalization, and feature engineering.
• Intellectual curiosity: you enjoy reading papers, keeping up with the latest in ML/AI, and experimenting with new ideas.
• The ability to communicate complex ideas clearly and collaborate effectively in a high‑performance team.

Pre’s:

• MLOps pipelines and tools (e.g., MLFlow, ClearML, Weights & Biases).
• High-performance computing and GPU optimization (e.g., CUDA, TensorRT).
• LLMs and related techniques like Retrieval-Augmented Generation (RAG).
• Agentic AI applications and their surrounding toolchains (e.g., LangChain, Haystack)

Benefits

• An opportunity to work beside the best in the field
• Competitive base salary based on experience
• Excellent variable pay based on performance
• Outstanding performance is also rewarded with shareholding in the company
• Relocation package when moving across states
• Training period in Amsterdam to get to know the team
• Comprehensive benefits package including medical, dental, and vision insurance
• Meals during work hours
• Social events and after-work drinks