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Quantitative Engineer Position
2 weeks ago
Company Overview
Alipes ApS has been a market leader in automating financial markets since our inception in 2008. We have pioneered fully automated natural language processing systems to read and interpret financial news.
We are focused on building a world-class machine learning engineering workflow, ensuring seamless training, deployment and monitoring of our predictive models. Your work will be instrumental in further developing the infrastructure that transforms massive unstructured financial data sets into production-ready inference models that drive real-time trading decisions.
Job Responsibilities
- Distributed Model Training: Designing and optimizing infrastructure to support distributed model training and experiment tracking.
- Data Pipelines: Building and automating robust data pipelines for dataset generation and feature engineering, while enabling data version control.
- Software Development: Developing software for rapid experimentation and deployment, including automated testing, continuous integration, and delivery.
- Model Deployment: Improving model deployment workflows, focusing on minimizing latency, ensuring reproducibility, and enabling fast iterations.
About the Team
You will join a tight-knit modeling team with passionate quantitative researchers covering 8 nationalities – fourteen PhD's and three MSc's with expertise in statistical analysis, mathematical modeling and machine learning. We enjoy collaboration and are always willing to lend a helping hand.
About You
- Fluency with computer science fundamentals – data structures and algorithms.
- Experience working with "out-of-core" datasets and training distributed models.
- Experience with Python, in particular the data preprocessing, ETL pipelines and distributed systems.
- Familiarity with strongly typed languages like C# or C/C++ or Rust.
- Experience working with the full Machine Learning stack from data generation through model training and real-life validation and monitoring.
- Experience with distributed computing frameworks (for example Spark, Ray or Dask).
Benefits
- Flat hierarchy and high levels of trust and autonomy.
- Exciting problems to solve.
- Collaborative team made up of really smart and curious people.
- Nice office in central Copenhagen with a hybrid work model.
- Pension, Health Insurance and 30 days of vacation.
