Deep Learning Researcher — AI for Trading & Markets

IMC Trading; New York (NY); On-site; USD 270,000 - 330,000; Full time

Job summary

IMC Trading is seeking Deep Learning Researchers to join its growing team in New York. You will develop state-of-the-art deep learning techniques at the intersection of AI and markets, collaborating with senior researchers from idea to production deployment.

The ideal candidate has a strong foundation in modern AI and machine learning research, gained through graduate study or internships. Prior finance experience is not required; a rigorous scientific mindset and a drive to learn are essential

Qualifications

• PhD, masters, or bachelor’s degree in a quantitative field to start full time in Feb or Aug 2027 or a postdoc.
• Demonstrated experience in deep learning research or applied ML with publications for PhD candidates.
• Hands-on with modern DL architectures (transformers, sequence models, self-supervised learning).

Responsibilities

• Build and improve deep learning models to enhance trading performance across asset classes.
• Contribute to research in representation learning, transformers, foundation models, generative AI, reinforcement learning.
• Support data curation, feature representation, and self-supervised/multimodal learning.
• Contribute to training infrastructure and deployment pipelines.
• Stay current with academic and industry developments and share findings with the team.

Skills

Deep learning research

Transformers

Python programming

DL frameworks

Communication skills

Education

PhD/MS/BS in CS/ML/AI/Math/Stats/Engineering

Tools

PyTorch

TensorFlow

JAX

Job description

IMC Trading is seeking Deep Learning Researchers to join its growing team in New York. You will develop state-of-the-art deep learning techniques at the intersection of AI and markets, collaborating with senior researchers from idea to production deployment.

The ideal candidate has a strong foundation in modern AI and machine learning research, gained through graduate study or internships. Prior finance experience is not required; a rigorous scientific mindset and a drive to learn are essential