TRAINED ON THE MARKET. TESTED IN IT.
Machine learning and AI sit at the core of our entire research and trading workflows. We use them not only to generate signals, but to build the tools, algorithms, strategies, and production agents that help us trade markets. Our researchers engineer features, train predictive models on market data, design adaptive systems, and apply techniques from reinforcement learning, deep learning, LLMs, NLP, and optimization. The result is a research environment where ideas are tested quickly, refined continuously, and validated directly in live markets.
SMARTER MODELS. STRONGER SIGNALS. BETTER TRADES.
For researchers who want their work to move into systems that operate at a global scale, IMC offers an environment where high-compute machine learning meets one of the world's most challenging real-time decision-making domains. We invest in our technology and people providing meaningful research with measurable impact, access to large-scale datasets and production systems, and the freedom to explore novel machine learning approaches that can transition quickly into production.
HOW ML IS APPLIED AT IMC
- Predictive modelling
We use ML to forecast market behaviour and identify trading opportunities, training models on huge, noisy, real-world datasets across multiple asset classes.
- High-speed experimentation
Our infrastructure lets you test and iterate ideas quickly, at scale, with real-time feedback from live markets. See your model’s impact quickly, often within hours.
- Agentic AI in production
Our engineering, trading, and research teams are embedding agents into workflows across our tech stack – with the compute power to match.
- Cross-team research
Our global teams collaborate to push the boundaries of what AI can achieve, with the autonomy and ownership to tackle problems that have a real impact.
FREQUENTLY ASKED QUESTIONS
We're a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Our teams build algorithms and systems that trade on markets around the world using our own capital and technology.
We embed ML across our entire research and trading workflow, from forecasting market behaviour and expanding feature sets, to embedding agents across our systems. Experience in RL, DNNs, LLMs, NLP, optimisation, or AI systems translates directly to the problems we're solving.
Your research won't wait for approvals or product roadmaps. You're working with large-scale, real-world data, with tight feedback loops and the autonomy to push ideas into production quickly. The problems are hard, the pace is fast, and you'll see the results of your work directly.
Collaboration is a huge part of how we work. Engineers, traders, and researchers sit side by side, constantly testing new ideas. It's fast-paced but team-focused, you're not siloed, and your work has visibility across the organisation.
Energetic, collaborative, and very hands-on. People are given real ownership early on and your work has visible impact. We love experimentation and continuous improvement, and everyone's ideas can directly influence how we trade and build technology.
Not at all. Many of our researchers join from fields completely outside finance. We'll teach you what you need to know about markets.
ML Researchers focus on building and refining models that improve predictive power. Quant Researchers focus on understanding markets and developing trading strategies. There's a lot of overlap in skills, and both roles contribute to how we trade, together they create a strong research environment.