Machine Learning Research and Engineering

Paris, 75, FR

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ABOUT CFM

Founded in 1991, we are a global quantitative and systematic asset management firm applying a scientific approach to finance to develop alternative investment strategies that create value for our clients.

We value innovation, dedication, collaboration, and the ability to make an impact. Together, we create a stimulating environment for talented and passionate experts in research, technology, and business to explore new ideas and challenge existing assumptions.

ABOUT THE ROLE

The Team

In close collaboration with the quantitative execution research team, the Trading Core & Model Technology (TCM) team is responsible for maintaining and developing a C++/Python stack dedicated to execution trading strategies.

Mostly C++ applications:
Feed handlers to distribute real-time, low-latency market data to automatons.

Execution libraries used by tick-by-tick trading automatons.

Indicators used for execution signals.

Python/C++ applications:
A tick-based machine learning pipeline used for execution strategies.

Data collection for the calculation and distribution of execution cost analysis metrics.

Analytical reports for execution research and compliance.

The team is also responsible for optimizing the tick to trade latency: from real-time market data reception to order sending and for building new ML execution models.

CFM is looking for an experienced and talented Machine Learning Research and Engineering expert

to build new ML models to feed CFM's execution strategies.

contribute to the maintenance and improvement of this ML pipeline.

The Mission

As a ML expert, and in collaboration with your team — particularly the machine learning experts who drive the evolution of this pipeline — you will participate to the development of this tick-based ML pipeline by:

Implementing new features in C++.

Improving the data generation part of the pipeline (enrich indicators, fine tune data sets)

Improving the training part of the ML pipeline (explore, propose, implement and evaluate the performance of new ML models, packages and frameworks)

Improving the production part of the pipeline (optimize inference latency, realize non regression tests, participate in the maintenance of this pipeline)

The candidate should have both a research mindset to explore new ML ideas, frameworks and evaluate them rigorously and full Computer Science engineering abilities to contribute to the maintenance and improvement of industrial research to production pipeline.

Key Responsibilities

ML Research and Engineering:
Explore and propose new ML ideas in collaboration with TCM and Execution teams

Implement and evaluate new ML ideas, data, models, frameworks and inference.

Participate in the maintenance of the platform (non-regression tests, migrations..)

Qualifications / Required Skills

PhD (or equivalent experience) in Machine Learning, Computer Science, Data Engineering, or a related field (experimental or theoretical science, mathematics, physics, statistics, economics, etc.)

Understanding of the ins and outs of machine learning algorithms

Experience with applied machine learning on large datasets

Proficiency in programming languages: a minimum of three years of experience in Python (and classical data and ML libraries, pandas/polars, scikit-learn, PyTorch, TensorFlow…) and experience in C++ is required but candidates with significantly more experience will be considered with great interest.

Although a high interest in finance is crucial, no prior knowledge in the field is needed.

Experience with Linux.

Proficiency in both French and English.

Excellent collaboration and communication skills.

Adaptable and rigorous, capable of working in a rapidly evolving environment.

Extra

Experience with Cloud (AWS or others).

Experience with SQL.

EQUAL OPPORTUNITIES STATEMENT

We are continuously striving to be an equal opportunity employer, and we prohibit any discrimination based on sex, disability, origin, sexual orientation, gender identity, age, race, or religion. We believe that our diversity, breadth of experience, and multiple points of view are among the leading factors in our success.

CFM is a signatory of the Women Empowerment Principles.