Campus AI Research Engineer: FinTech Deep Learning

Aplaro Ltd; New York (NY); Híbrido; USD 255.000 - 345.000; Tempo integral

Benefícios oferecidos por esta vaga

Discretionary bonus eligibility

Medical insurance

Dental insurance

Vision insurance

HSA/FSAs

Retirement plan with employer match

Paid vacation and holidays

Parental leave

Wellness programs

Resumo da vaga

Jump Trading Group seeks research scientists to push the boundaries of machine learning in global financial markets. You will take an open-ended research project from concept to production, building scalable ML systems and reusable frameworks in Python, C++, and CUDA while collaborating with researchers, quants, and engineers.

The role rewards strong publication records in major ML venues and practical experience applying DL techniques to real data.

Qualificações

• Strong publication record at top ML conferences (ICML/NeurIPS/AAAI).
• Deep understanding of modern ML and DL architectures (transformers, language modeling).
• Solid development skills in Python and C++.
• Experience with ML frameworks such as PyTorch, JAX or TensorFlow.

Responsabilidades

• Apply state-of-the-art techniques to complex domains in finance.
• Collaborate with researchers, quants, and engineers to build reusable ML frameworks.
• Optimize training pipelines for HPC resources.
• Integrate ML models into latency-sensitive production systems.
• Work with C/C++/Python/CUDA across large-scale ML systems.
• Improve productivity by shortening research iteration cycles.
• Other duties as assigned.

Conhecimentos

Strong publication record

Machine learning

Python

C++

PyTorch

JAX

TensorFlow

CUDA

Quantitative problem solving

Ferramentas

CUDA

Descrição da vaga

Jump Trading Group seeks research scientists to push the boundaries of machine learning in global financial markets. You will take an open-ended research project from concept to production, building scalable ML systems and reusable frameworks in Python, C++, and CUDA while collaborating with researchers, quants, and engineers.

The role rewards strong publication records in major ML venues and practical experience applying DL techniques to real data.