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updated 1 month ago

Campus AI Research Engineer (Fintech)

250 000 - 300 000$
Work type
fulltime
Grade
junior
English
c1
Country
US
This vacancy is from Hirify.Global listVacancy from Hirify Global, list of international tech companies
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Job description

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TL;DR
Campus AI Research Engineer (Fintech): Building and optimizing state-of-the-art ML systems for quantitative finance with an accent on high-performance computing and low-latency inference. Focus on developing scalable AI frameworks, optimizing training pipelines, and integrating complex models into production trading environments.

Location: Must be based in Chicago or New York

Salary: $250,000 – $300,000 per year

Company

hirify.global is a global quantitative research and trading firm that leverages advanced statistical analysis and cutting-edge technology to solve complex problems in financial markets.

What you will do

  • Apply state-of-the-art AI/ML techniques to complex financial domains.
  • Collaborate with researchers and quants to build flexible, reusable AI/ML frameworks.
  • Optimize training pipelines to maximize the efficiency of HPC resources.
  • Integrate models into production systems with strict latency requirements.
  • Develop large-scale systems using C, C++, Python, and GPU-accelerated languages.
  • Improve research productivity by reducing iteration cycle times.

Requirements

  • Proficiency in Python and/or C++
  • Expertise in GPU or accelerator programming (CUDA, Triton, SYCL, ROCm)
  • Experience with ML frameworks like PyTorch, JAX, or TensorFlow.
  • Experience building AI/ML systems at scale with large datasets.
  • Excellent written and verbal communication skills in English
  • Must be eligible for CPT/OPT or require work visa sponsorship

Culture & Benefits

  • Collaborative, team-oriented environment focused on innovation and scientific boundaries.
  • Opportunity to work on impactful projects in a fast-paced quantitative finance setting.
  • Support for international students including CPT/OPT and visa sponsorship.
  • Exposure to large-scale systems and high-performance computing infrastructure.

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