AI Research Intern: Deep Learning, LLMs & RL for Finance

Two Sigma; New York (NY); On-site; USD 228,000 - 250,000; Full time

Job summary

Two Sigma is seeking creative researchers for a summer project applying general machine learning, deep learning, large language models, and reinforcement learning to complex financial data problems. MS or PhD candidates in penultimate year are encouraged to apply, with opportunities to write code, run experiments, and discuss results in a collaborative research setting.

You will work under guidance on a ~10-week project, leveraging Python and ML frameworks, data pipelines, and cloud compute,

Qualifications

• Working toward an MS or PhD in CS, Engineering or related STEM field.
• Strong Python, TensorFlow/PyTorch; familiarity with Rust/Java is a plus.
• Experience with DL, LLMs and RL in internships or coursework.
• Experience building data pipelines for large noisy data in ML contexts.
• Research experience with publications (NeurIPS/ICML/ICLR or similar) is a plus.
• Solid understanding of basic statistics and ML fundamentals.
• Experience with cloud environments and multi-machine setups.
• Curiosity about financial data modeling in a collaborative setting.

Responsibilities

• Develop techniques/infrastructure for a project over ~10 weeks during summer.
• Write code, run experiments, and discuss results using modern AI/ML tools.
• Collaborate to improve understanding of how financial data shapes outcomes.

Skills

Python programming

TensorFlow

PyTorch

Rust

Java

Deep Learning

LLMs

Reinforcement Learning

Data pipelines

Statistical understanding

Cloud computing

Multi-machine setups

Research experience

Financial data modeling interest

Education

MS/PhD candidate (penultimate year)

Job description

Two Sigma is seeking creative researchers for a summer project applying general machine learning, deep learning, large language models, and reinforcement learning to complex financial data problems. MS or PhD candidates in penultimate year are encouraged to apply, with opportunities to write code, run experiments, and discuss results in a collaborative research setting.

You will work under guidance on a ~10-week project, leveraging Python and ML frameworks, data pipelines, and cloud compute,