Graduate Deep Learning Researcher - London
Salary not listed • London, United Kingdom • Full-time
Posted 3mo ago
This job has been open for more than 60 days. It may no longer be actively hiring, so check with the company before putting a lot into an application.
Job Location
London, United Kingdom
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Research Engineer
About the job
IMC is seeking Deep Learning Researchers to join our growing team. As a Deep Learning Researcher, you will develop and apply state-of-the-art deep learning techniques at the intersection of AI and markets. You will help accelerate our efforts in areas such as modern neural network architectures and representation learning, improving our large-scale AI models that increasingly shape our trading. You will work closely with senior researchers to gain exposure to the full research lifecycle, from initial idea to production deployment. The ideal candidate has a strong foundation in modern AI and machine learning research, gained through post-graduate study or internships. Prior financial industry experience is not required. We are looking for someone who brings rigorous scientific thinking and a drive to learn, and who wants to grow alongside experienced researchers as we build a world-class deep learning capability at IMC.
Responsibilities
- Build and improve deep learning models to enhance trading performance across multiple asset classes, under the guidance of senior researchers.
- Contribute to research in areas such as representation learning, transformers, foundation models, generative AI, and reinforcement learning.
- Support large-scale data curation, feature representation, and self-supervised and multimodal learning from structured and unstructured datasets.
- Contribute to shared training infrastructure and deployment pipelines.
- Stay current with academic and industry developments in deep learning and share relevant research with the team.
Requirements
- MSc (PhD preferred) in Machine Learning, Statistics, Deep Learning, Probabilistic Programming, or a related quantitative field.
- Currently in final year of study, graduating in 2027.
- Demonstrated experience in deep learning research or applied machine learning.
- Hands-on experience with modern deep learning architectures, such as transformers, sequence models, representation learning, self-supervised learning, and/or generative models.
- Solid understanding of the theoretical foundations of deep learning, optimization, statistical learning, and neural network training dynamics.
- Strong programming skills in Python.
- Hands-on experience with at least one modern deep learning framework, such as PyTorch, JAX, or TensorFlow.
- Strong communication skills with the ability to explain technical ideas clearly to both technical and non-technical audiences.