Associate, Machine Learning Engineer

3 months ago

Responsibilities

Build, evaluate, and improve AI-powered financial services applications with cross-functional teams.
Design and implement machine learning models and algorithms for business problems.
Work with large language models and analyze their behavior and failure modes.
Test and evaluate LLM-powered applications, including defining success metrics and analyzing failures.
Apply machine learning, statistics, and experimental design principles to model behavior.
Communicate project goals and findings to product, engineering, business, and other stakeholders.
Support responsible AI practices involving privacy, security, and appropriate automation.
Document project progress and provide support and mentorship to junior team members.

Bachelor’s degree in a technical field such as computer science, machine learning, or mathematics, or equivalent practical experience.
Experience contributing to production-level software development through employment, internships, research, or substantial personal projects.
Strong Python programming skills and the ability to write clear, tested, and maintainable code.
Hands-on experience with web services, data integration, testing, logging, and monitoring.
Practical experience 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.
Strong technical documentation, communication, and collaboration skills.
Interest in applying AI responsibly in financial services.
Familiarity with agentic workflows, evaluation tools, and cloud deployment is preferred.

1,001-5,000 employees