Member of Technical Staff - AI
About the Role
We're building the future of human opportunity matching, and we need visionaries who can turn data into destiny. As a Founding AI Engineer, you'll be at the forefront of a revolution that's redefining how people connect to life-changing opportunities.
Imagine a world where the perfect advisor finds the exact startup that needs their expertise. Where speakers who can electrify a room are matched with the conferences hungry for their insights. Where talent and companies find each other not through chance, but through intelligent design.
That's the world we're building—and we want you to help us build it.
Key Responsibilities
Design and deploy AI systems that weave together people, companies, and products into a living knowledge graph of opportunity
Develop sophisticated matching algorithms that go beyond keywords to understand the true essence of expertise and potential
Build systems that process, analyze, and connect vast oceans of public data, turning information into insight
Craft learning models that improve with every match, continuously refining our understanding of what makes for perfect connections
Engineer pipelines that transform raw data into career-defining moments for users across diverse industries
Cross team collaboration with the data engineer and others to develop the data structures that can store and serve structured insights.
Required Experience
A data detective with 3-5 years of experience working with machine learning algorithms as well as real-world datasets in production environments
Demonstrated experience fine-tuning large language models (LLMs)
3-5 years of programming experience with Python and relevant ML frameworks
Strong understanding of machine learning fundamentals
Experience with data preprocessing, feature engineering, and model evaluation
Proficiency in SQL and experience working with database systems
MS/Bachelor's degree in Computer Science, Information Systems, or related field
What Will Set You Apart
Ideally have experience working with real-world finance datasets
Experience working with vectorized databases and RAG
Experience deploying ML models to production and creating scalable ML pipelines
Knowledge of cloud platforms (such as AWS) and their ML offerings
Contributions to open-source ML projects or research publications
Master's or PhD in Machine Learning, AI, or related field