Associate, Machine Learning Engineer

Cantor Fitzgerald•New York, NY

About The Position

We are seeking an early-career engineer to join our team and play a vital role in developing and enhancing AI-powered applications for our financial services business. The ideal candidate will have a solid foundation in software development, hands-on experience with modern AI tools, and a keen interest in understanding the behavior of language models in real-world applications. As an Associate, you will have the opportunity to work closely with our experienced engineers and contribute to the growth and success of our innovative AI initiatives.

Requirements

Bachelor's degree in a technical field (computer science, machine learning, mathematics, etc.) or equivalent practical experience.
Experience contributing to production-level software development, internships, research, or substantial personal projects.
Strong programming skills in Python, with a focus on writing clear, tested, and maintainable code.
Hands-on experience with web services, data integration, testing, logging, and monitoring.
Practical knowledge of building with LLMs and understanding common failure modes.
Ability to test, evaluate, and improve LLM-powered applications.
Grounding in machine learning, statistics, and experimental design, with a knack for technical documentation.
Excellent communication skills and a collaborative mindset.
Interest in applying AI responsibly in financial services.

Nice To Haves

Familiarity with agentic workflows, evaluation tools, and cloud deployment is a plus.

Responsibilities

Collaborate with a cross-functional team to build, evaluate, and improve AI-powered financial services applications.
Design and implement machine learning models and algorithms to solve complex business problems.
Work with large language models (LLMs) and understand their behavior and potential failure modes.
Conduct testing and evaluation of LLM-powered applications, analyzing failures and defining success metrics.
Apply machine learning, statistics, and experimental design principles to reason about model behavior.
Communicate effectively with product, engineering, and business partners to align on project goals.
Ensure responsible AI practices are followed, considering privacy, security, and appropriate automation.
Stay updated with the latest advancements in AI and machine learning technologies.
Document and present project progress and findings to stakeholders.
Provide support and mentorship to junior team members as needed.