AI/ML Engineer — Financial Services & LLM Apps

Cantor Fitzgerald Ireland Ltd

New York (NY)

On-site

USD 120,000 - 150,000

Full time

28 hours ago
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Benefits offered by this job

Health insurance
Vision insurance
Dental insurance
Paid time off
401(k) retirement

Job summary

Cantor Fitzgerald L.P. is seeking an early-career engineer to help build, evaluate, and improve AI-powered applications for a large-scale financial services business.

The role emphasizes strong software fundamentals, hands-on experience with modern AI tools, and curiosity about language-model behavior in real products. Ideal candidates bring production software experience, proficiency in Python, and familiarity with LLM workflows, testing, and evaluation to ensure reliable, well-grounded

Qualifications

  • Bachelor's degree in a technical field or equivalent practical experience.
  • Experience contributing to production or production-like software.
  • Strong programming ability in Python with clean, tested code.
  • Experience with web services, data integrations, testing, logging, and monitoring.
  • Hands-on experience with LLM tools/frameworks and awareness of failure modes.
  • Experience testing/evaluating LLM-powered apps and improving prompts.
  • Background in ML, statistics, and experimental design.
  • Strong communication with product, engineering, and business partners; focus on responsible AI in finance.

Skills

Python programming
Production software experience
Web services & data integrations
LLM tooling frameworks
LLM testing & evaluation
ML/statistics foundations
Communication with product/engineering
Responsible AI awareness

Education

Bachelor's degree

Job description

Cantor Fitzgerald L.P. is seeking an early-career engineer to help build, evaluate, and improve AI-powered applications for a large-scale financial services business.

The role emphasizes strong software fundamentals, hands-on experience with modern AI tools, and curiosity about language-model behavior in real products. Ideal candidates bring production software experience, proficiency in Python, and familiarity with LLM workflows, testing, and evaluation to ensure reliable, well-grounded

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