Machine Learning Engineer

Machine Learning Researcher — real feedback cycles!

Do you want to see your models make decisions in live financial markets — not sit in a notebook waiting for a quarterly review? Are you as comfortable thinking about data pipelines and calibration frameworks as you are about model architecture?A market-leading quantitative trading firm is looking for a Machine Learning Researcher to join their modelling team in Copenhagen.

They've been automating financial markets since 2008, and ML sits at the core of how they operate. This isn't a role where you hand off to an engineering team and wait. You'll own the work from data generation through to deployment — and in this environment, that cycle can be measured in hours, not months.

What you'll do▸ Lead modelling workflow — build and improve the frameworks that turn massive financial datasets into predictive models that move with the markets.▸ Develop and optimise — work on calibration and benchmarking frameworks, data preparation pipelines, and dataset generation at scale.▸ Ship novel architectures — prototype and release new predictive models with a particular focus on time-series approaches.▸ Work with real data, real stakes — your models get validated against live markets.

Feedback is immediate and unambiguous.▸ Collaborate closely — work alongside quant researchers, software developers and traders who all write code and understand the craft.

The team

Eighteen quantitative researchers across six nationalities — thirteen PhDs and five MScs — with expertise spanning statistical analysis, mathematical modelling and machine learning. No red tape, no sales layer between you and your work. Technical discussions are valued, ownership is expected, and the team genuinely enjoys what it does. Successes are celebrated.

What they're looking for✓ Strong foundations in mathematics and statistics — you think rigorously, not just empirically. ✓ End-to-end ML experience — from data generation and wrangling through model calibration, validation and live monitoring.

You've built systems that run in production, not just experiments that ran in a notebook.✓ Research depth — whether from academia or industry, you can point to work where you designed experiments, validated results, and drew meaningful conclusions from data.

Published research is a strong positive signal but not a requirement.✓ Solid Python skills — data-wrangling, numerical programming, production-quality code.✓ Computer science fundamentals — you understand what's happening under the hood.✓ A scientific, inquisitive mindset — you ask why the model works, not just whether it does.

Financial markets knowledge is a plus but not a prerequisite — the team cares more about how you think and build than which domain you come from. If your background is in physical sciences, engineering, or applied mathematics and you've been working on hard prediction problems with real data, we want to hear from you.

Nice to have: If you have experience with time-series forecasting, out-of-core datasets, PyTorch, TensorFlow, XGBoost or CatBoost, C# or C/C++, and a PhD or MSc in engineering, physics, computer science, mathematics or economics that is all awesome!

• What they offer💰 Competitive compensation package
• Pension, health insurance and 30 days of vacation
• Modern harbourfront office in Copenhagen (Nordhavn)
• Hybrid working model - 4 days in the office, 1 day remote
• Flat hierarchy — high trust, high autonomy, real freedom to make decisions
• Short feedback cycles — from inception to deployment can be hours, not quarters
• Strong team culture with company events and trips