Machine Learning Engineer
Capital Fund Management Järvenpää, Uusimaa, Finland
Financial Services · 201-500 employees
About the role
You will develop and maintain a tick-based machine learning pipeline by implementing new features in C++ and optimizing data generation and training processes. Additionally, you will collaborate with the execution research team to build and evaluate new ML models to support investment strategies.
What they look for
Requirements
The role requires a PhD or equivalent experience in a quantitative field along with strong proficiency in Python and C++. Candidates must have experience applying machine learning to large datasets and possess excellent communication skills in both English and French.
Full description
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
CFM is looking for an experienced and talented Machine Learning Research and Engineering expert
- to gather the needs of execution research team and implement evolution of the pipeline accelerating their research
- contribute to the maintenance and improvement of this ML pipeline.
- to build new ML models to feed CFM's execution strategies.
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, a full Computer Science engineering abilities to contribute to the maintenance and improvement of industrial research to production pipeline and a client oriented mindset to gather the needs of execution research team and implement evolutions requested
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.
FOLLOW US
Follow us on Twitter or LinkedIn or visit our website to find out more about CFM.
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