Quant jobs / IMC Trading

Deep Learning Researcher

A deep learning research role advancing large-scale models that feed trading decisions. It sits in a team building deep learning research and infrastructure across the firm.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Develop and test new neural architectures for market state prediction
Work on representation learning and self-supervised pre-training on market data
Prototype models for signal generation, execution and portfolio construction
Curate large training datasets and features
Turn research into scalable systems with traders and engineers

What they ask for

Required

PhD or Master's in a quantitative field
3+ years of deep learning research
Transformers and sequence models
Optimisation and learning theory
Distributed training
Python with PyTorch, JAX or TensorFlow

Preferred

Large-scale pre-training experience

Education: PhD or Master's in CS, machine learning, AI, maths, statistics or engineering.
Experience: 3+ years of deep learning research; no finance experience required
Languages and tools: Python
PyTorch
JAX
TensorFlow
Markets: multi-asset

How to prepare

Reproduce a sequence-model paper on financial or other noisy time series
Study why ML models overfit in low signal-to-noise data
Practise distributed training with PyTorch
Learn how predictions become trades (costs, sizing, execution)

What to study

The NLP and ML Quant Researcher roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on IMC Trading’s site before applying: requirements, location and pay can change after we check them.

View the posting on IMC Trading’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with IMC Trading and doesn’t handle applications.