Machine Learning Quant

Davinciderivatives

Amsterdam

On-site

EUR 70,000 - 90,000

Full time

14 days+

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Benefits offered by this job

Competitive base salary
Variable pay and growth opportunities
Relocation package
Access to in-house gym
Social events
Game room access

Job summary

Davinciderivatives in Amsterdam seeks a Machine Learning Engineer passionate about ML and AI to develop, test, and deploy cutting-edge models for trading systems. You'll collaborate with a team of researchers and traders to build innovative solutions that impact financial performance.

Ideal candidates should have a PhD or MSc, proficiency in Python, and experience with ML frameworks. The position offers a competitive salary, the opportunity for ownership of models, and benefits including relocation support and in-house amenities.

Qualifications

  • Strong academic background in Machine Learning, AI, Statistics or related field.
  • Hands-on experience with ML/AI models for time series forecasting.
  • Curiosity about trading and financial dynamics.

Responsibilities

  • Develop and deploy ML/AI models for prediction and detection.
  • Work with teams to implement insights into trading strategies.
  • Evaluate new ML techniques for financial applications.

Skills

Machine Learning
AI
Python
Statistical Modelling
Software Development

Education

PhD or MSc in relevant field

Tools

PyTorch
TensorFlow
Docker
PostgreSQL

Job description

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.
  • Take full ownership of your models and strategies - from signal research, feature engineering, and backtesting through to execution, live performance monitoring, risk assessment, and iterative improvement in production.
  • Analyze large, noisy, high‑frequency data streams; performing advanced feature engineering, and bias detection.
  • Collaborate with our systems and infrastructure engineers to ensure models are productionised efficiently and reliably.
Requirements
  • A strong academic background in Machine Learning, AI, Statistics, Computer Science, Mathematics, or a related field - typically a PhD or equivalent, or an MSc with significant relevant experience
  • Hands on experience building and deploying ML/AI models, especially for time series forecasting or anomaly detection.
  • Genuine curiosity about trading, market microstructure and financial dynamics
  • Proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow, 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.
  • Stays up to date on ML/AI literature and experiments with new ideas
  • The ability to communicate complex ideas clearly and collaborate effectively in a high‑performance team.
Preferred qualifications
  • MLOps pipelines and tools (e.g., MLFlow, ClearML, Weights & Biases).
  • High-performance computing and GPU optimization (e.g., CUDA, TensorRT).
Benefits
  • An opportunity to work beside the best in the field, with direct exposure to live trading - you own your models and strategies end-to-end, from research through to production
  • Competitive base salary based on experience
  • Excellent variable pay and growth opportunities
  • Outstanding performance is also rewarded with shareholding in the company
  • A relocation package when moving from abroad, including a relocation budget, flight coverage, house‑finding service and expat support
  • Meals during work hours
  • Social events and after‑work drinks
  • Reimbursement of travel costs
  • Access to the in‑house gym and chair massage
  • In‑house game room (pool table, board games and console games)
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