AI Research Scientist - Intern [2027 Summer]

Two Sigma; New York (NY); On-site; USD 227,500 - 250,250; Full time

Job summary

Two Sigma is seeking creative experts who want to apply general ML, deep learning, LLMs, and reinforcement learning to complex financial data problems. This opportunity is targeted at MS students in the penultimate year or PhD candidates with work experience.

You will develop techniques and infrastructure for summer projects, build experiments, run analyses, and collaborate with a team of scientists and engineers to improve understanding of how data influences markets.

Qualifications

• Pursuing MS/PhD in Computer Science, Engineering or related STEM field.
• Strong programming in Python with exposure to ML frameworks.
• Experience with Deep Learning, LLMs and/or RL via internships, coursework or research.
• Experience building data pipelines for large noisy datasets.

Responsibilities

• Develop techniques and/or infrastructure for a research project over a ~10 week summer period.
• Write code, run experiments, evaluate approaches, and discuss results with the team.

Skills

Python

TensorFlow

PyTorch

Deep Learning

LLMs

Reinforcement Learning

Cloud computing

Data pipelines

Statistics

Education

MS degree in CS/Engineering

PhD candidate

Job description

Position Summary

Two Sigma is a financial sciences company, combining data analysis, invention, and rigorous inquiry to help solve the toughest challenges in investment management, securities, private equity, and venture capital.

Our team of scientists, technologists, and academics looks beyond the traditional to develop creative solutions to some of the world’s most complex economic problems.

We are looking for creative experts who are interested in applying general Machine Learning and specifically Deep Learning, Large Language Models, and Reinforcement Learning techniques to many types of problems in complex systems, and particularly those with large amounts of noisy data.

This role is only open to MS with work experience and PhDs, both in their penultimate year of study.

You Will Take On The Following Responsibilities

• Develop effective techniques and/or infrastructure for a specific project/idea under guidance of an experienced member of the team over a time of roughly 10 weeks during the summer.
• In our research environment, you will write code, use the latest AI and machine learning tools, run experiments, discuss approaches and results with others, and generally develop techniques and processes to help improve our understanding of how financial data influences the world around us.

You Should Possess The Following Qualifications

• Working toward a degree in Computer Science, Engineering, or other STEM field, preferably in a PhD program, or in a Master’s program with some prior work experience.
• Excellent programming skills in Python (familiarity with Rust/Java is a plus) and deep knowledge of Tensorflow and/or PyTorch.
• Internships/work/course experience using Deep Learning, LLMs and/or Reinforcement Learning.
• Preferably practical experience writing and using data pipelines to handle large amounts of noisy data for machine learning problems.
• Preferably some relevant research experience (that may have led to publications at NeurIPS, ICML, ICLR or similar).
• Understanding of basic statistics.
• Experience with cloud computing environments and multi-machine setups.
• Curiosity and interest in learning about financial data modeling in a collaborative environment.

The weekly base pay for this role will be between $5,000/Week (MS) and $5,500/Week (PhD) based on academic degree conferred. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans, and 401(k) contributions. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.

We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.