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High performance, low latency, global markets… You know where this is going, right? Yup, trading. Business is booming and this company is ready to make the most of it. It’s a place of high pace and quick decisions, perfect for Quants who really love to make things happen. Perfect for you.

You have my attention

The Netherlands has always had a strong reputation in financial trading, and this company isn’t about to fall behind. As a High-Frequency Trading firm, it breathes technology. For every trader on the floor, there are at least two developers. Make no mistake, IT is their core business. Because in such a highly competitive market, performance, speed, and reliability are key.

What about the role?

As a Machine Learning Engineer, you are part of a small, highly capable group of engineers supporting a larger team of researchers. You take full ownership from design to deployment and maintenance, working on systems that span real-time ML inference, large-scale data infrastructure and the research platform that powers discovery. The scope is broad and hands-on, requiring you to go deep across the stack rather than specialize in just one area. That’s exactly what makes the role both challenging and rewarding.

You design and evolve real-time inference systems that deliver predictions with ultra-low latency in a production trading environment. At the same time, you build and maintain petabyte-scale data and ML infrastructure, enabling everything from ingestion at scale to end-to-end pipeline orchestration. Collaboration is key. You contribute ideas, challenge assumptions and help shape the technical direction, all within a culture where quality, ownership and mutual respect define how work gets done.

Let’s check my CV!

You’re fluent in a systems language like Rust or C++ and combine that with strong Python skills to operate across the full stack. You’ve built and run real production systems with uptime requirements, latency constraints and real impact when things go wrong. You bring depth in at least one domain, whether that’s ultra-low-latency systems, ML infrastructure or high-throughput data engineering, while staying broadly skilled across the rest. Working in small, fast-moving teams feels natural to you, whether that’s a startup, trading firm or similar environment.

You have 3 years experience building and operating ML systems in production, working with frameworks like PyTorch, JAX or ONNX, not just for training but for deployment and integration at scale. You’re comfortable with asynchronous and multi-threaded programming and understand high-throughput data pipelines and scheduling. With a solid foundation in mathematics and statistics, you collaborate effectively with researchers and take ownership of what you deliver, always looking for ways to improve.

So this trading thing, what does it pay?

Pretty good, to be honest. Starting with a base salary between €120.000 and €140.000 gross per year, excluding secondary benefits. And those benefits? They’re second to none..Think fully catered lunch every day, flexible working, and a royal end-of-year bonus. Remember, I said speed was key? So, what are you waiting for? Click apply!