Internship: Quantitative Software Engineer (m/f/d)
Berlin
Full-time
Intern / Student
About the position
We are seeking an ambitious and driven intern to join our dynamic team in Berlin. In this role, you will collaborate with quantitative researchers, machine learning experts, and software engineers to advance our cutting-edge quantitative investment platform. This is a hands-on role focused on portfolio construction — the process of translating AI-generated alpha forecasts into risk-controlled, investable portfolios. You will work with constrained optimization, global fundamental risk models, and transaction cost modeling to ensure that stock-level predictions are efficiently captured in real portfolios while respecting risk, regulatory, and operational constraints.
Your Mission
- Maintain and Improve Portfolio Construction Infrastructure: Extend and improve existing software systems for constrained portfolio optimization, including the design and implementation of new constraints, strategy configurations, and constraint relaxation policies.
- Support Live Portfolio Operations: Contribute to the production rebalancing pipeline — including portfolio state ingestion, corporate action handling, infeasibility diagnostics, and constraint relaxation. Investigate discrepancies between live portfolio behavior and backtested expectations.
- Data Quality & Validation: Investigate and resolve data inconsistencies in optimization inputs — including market data, asset mappings, and security classifications — ensuring the integrity of the portfolio construction pipeline.
- Model Transaction Costs and Taxes: Develop and refine models that account for transaction costs and taxes within the portfolio optimization process.
- Performance Analysis & Transparency: Monitor and improve transfer coefficient and risk model bias to maximize signal expression and ensure well-calibrated risk forecasts. Extend existing performance attribution and risk decomposition tools with new diagnostics.
- Drive Research & Innovation: Research and implement novel strategy configurations and adaptive rebalancing frameworks that respond to evolving risk regimes and alpha signal decay.
- Optimize Code for Performance: Improve efficiency and scalability by optimizing and parallelizing code, enabling high-performance execution of large-scale backtesting.
- Ensure Code Quality: Write clean, modular, and maintainable code. Follow best practices in software development, including version control, unit testing, and peer reviews.
- Simplify and Streamline the Codebase: Refactor existing code to reduce complexity, improve readability, and ensure consistency for easier maintenance and scalability.
- Collaborate and Communicate: Work closely with quantitative researchers, machine learning practitioners, and software engineers. Explain complex ideas clearly to non-technical stakeholders.
Your Skillset
To thrive in this role, you should possess:
- A degree in a technical field such as Mathematics, Physics, Computer Science, Financial Engineering, or Statistics.
- Strong programming skills in Python. Solid foundations in linear algebra, applied statistics, and mathematical optimization — in particular an understanding of factor models, covariance estimation, and constrained optimization.
- Experience in collaborative Python development, including proficiency with tools for version control (Git), shell scripting (Zsh/Bash), and continuous integration (e.g., GitHub).
- The ability to write maintainable and well-tested code using tools like Pydantic and Pytest.
- Familiarity with portfolio theory and an interest in practical challenges such as transaction cost modeling, tax-aware investing, and feasibility analysis.
- Prior experience with portfolio optimization and analytics using global factor models (Axioma, MSCI Barra) is a plus.
- A keen interest in financial markets and the quantitative investment process.
- Team-oriented mindset with a preference for in-office collaboration.
Why us?
- An exciting and hands-on role with real impact on shaping the future of AI-driven sustainable investing.
- A collaborative company culture focused on quality, openness, and attention to detail in all areas of our work.
- The opportunity to work in an interdisciplinary team alongside experienced professionals in quantitative finance, software engineering, and machine learning.
- A modern loft office in Berlin (Prenzlauer Berg), healthy food options (coffee, juices, fruit, vegetables, sandwiches), and high-end Apple hardware.
- Internal workshops, unique learning opportunities across a wide range of domains, and fantastic team events.
- Additional benefits such as Urban Sports Club, as well as access to corporate benefits.
About us
We are a deep tech pioneer, providing AI-based investment solutions to our clients. Building on the best practices of quantitative asset management we tap the potential of machine learning for sustainable investments on capital market.
Our interdisciplinary team consists of experts in the fields of finance, computer science, software engineering, machine learning as well as mathematics, physics, and neuroscience. Ultramarin is embedded in the global AI community, through a close exchange with leading universities and as a member of Inquire Europe.
To date Ultramarin is one of the leading drivers for AI-based analyses and decision-making processes in asset management. Ultramarin has been founded in 2017, is headquartered in Berlin, with additional locations in Frankfurt and Munich, and is backed by leading international business angels and VCs.