Quant Infrastructure Student

Are you a talented hacker with a passion for data engineering and building things that actually run in production? Do you enjoy working close to the metal, solving real problems, and seeing your code go live within hours?

Then you might be the next Quant Infrastructure Student joining our team at Alipes!

About Alipes

At Alipes Capital, we have been a market leader in automating financial markets since our inception in 2008, pioneering fully automated natural language processing systems to read and interpret financial news.

To accomplish our goal of being the best at what we do, we are focused on building a world-class ML engineering workflow, ensuring seamless training, deployment and monitoring of our predictive models.

What you’ll do

You’ll help us build and improve the ML infrastructure powering our fully automated trading systems. Expect hands-on work with:

• Python tooling for data processing and rapid model experimentation.

• Scalable pipelines for dataset generation, feature engineering and model training.

• Distributed computing technologies (e.g., Ray, Kubernetes).

• Internal utilities that make it easier for researchers to prototype, validate and deploy models.

• Improving latency, reproducibility and monitoring in our deployment workflows.

You’ll work closely with quantitative researchers and ML engineers, contributing directly to production-grade systems.

About the team

You’ll join an informal, highly technical Quant team where ownership matters and good ideas move fast. We’re a tight-knit group of researchers across 9 nationalities, all with strong backgrounds in math, modeling, and machine learning - and everyone writes code. We collaborate closely with our software developers and traders, working together on models end-to-end and engaging deeply in the technical details that make them work.

About you

You don’t need years of experience, but you do need curiosity, strong fundamentals, and a willingness to build things that work. You are currently studying either a Bachelor's or Master's in Denmark. We’re looking for someone with:

• A scientific and inquisitive mindset.

• Solid understanding of computer science fundamentals (data structures & algorithms).

• Strong Python skills, especially around data preprocessing or pipeline building.

• Interest in distributed systems or ML Ops.

• Experience working with datasets that don’t fit in memory.

• Familiarity with at least one strongly typed language (C#, C/C++, Rust, etc.).

• Currently enrolled in a technical BSc/MSc program (CS, engineering, math, physics, etc.).

Nice to have

• Hands-on experience with ML workflows (dataset generation → training → evaluation).

• Exposure to distributed computing frameworks (Ray, Spark, Dask).

• Familiarity with containerization (Docker, Kubernetes).

• Experience with ML libraries like PyTorch, TensorFlow, XGBoost or CatBoost.

• Interest in algorithmic trading concepts.

• Personal projects that show you like to hack on things, automate stuff, or optimize pipelines.

What we can offer you

• Competitive benefits, including health insurance and 25 days of vacation.

• A modern office in Copenhagen (Nordhavn) with a flexible hybrid work model.

• A flat hierarchy with high levels of trust, autonomy, and freedom to make decisions.

• A valued role with unique responsibilities and plenty of room for creativity.

• Fast feedback and recognition of your contributions in a high-growth company.

• Strong team spirit - successes are celebrated with company events and trips.

Practicalities

To apply, please send us your CV, and attach your BSc and/or MSc grade transcripts to your application. If your profile looks like a good match, we will get in touch to coordinate an online technical test as a first step in the interview process.

If you have specific questions about the role, you are welcome to email us at [email protected]. Please do not send in your applications to this email address, as our interview team will not have visibility to review.