Deep Learning Research Intern - Summer 2027 - New York

Quant Blueprint LLC; New York (NY); On-site; USD 270,000 - 330,000; Full time

Benefits offered by this job

Accommodation provided

Job summary

Quant Blueprint LLC is seeking a dedicated student-intern to research deep-learning models, using large datasets and modern training infrastructure. Projects include representation learning, transformers, foundation models, generative AI and reinforcement learning with mentorship.

Applicants should be pursuing a Bachelor’s, Master’s or PhD in computing or a quantitative field, graduating in 2027–2028, with hands-on experience in Python and ML frameworks.

Qualifications

• Bachelor’s, master’s or PhD student in computing, ML or related field, graduating 2027–2028.
• Applied deep-learning experience with Python and ML frameworks; publications or open-source work is a plus.
• No finance experience required.

Responsibilities

• Research deep-learning models using large datasets and modern training infrastructure.

Skills

Applied deep-learning

Python

PyTorch

JAX

TensorFlow

Education

Bachelor’s, Master’s or PhD student

Tools

Python

PyTorch

JAX

TensorFlow

Job description

Research deep-learning models using large datasets and modern training infrastructure. Potential topics include representation learning, transformers, foundation models, generative AI and reinforcement learning, with support from a research mentor.

Requirements

Bachelor’s, master’s or PhD student in computing, machine learning or a related quantitative field, graduating September 2027–July 2028. Applied deep-learning experience, Python and PyTorch, JAX or TensorFlow; publications or open-source research are advantages. No finance experience required. In-person start: June 7, 2027.

Programme details

Accommodation is included; performance may lead to a graduate offer. One application per role per year.

Employer-published base pay

• USD 300,000 / year (annualized; prorated for the internship)