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Fin is an AI Customer Agent company building the highest-performing AI customer support agent on the market. The Machine Learning team is responsible for defining new ML features, researching algorithms, and rapidly prototyping solutions that reach customers. This is a product-focused team that partners closely with Product and Design to ship features to beta within weeks of successful offline testing.
As a Staff Machine Learning Scientist, you will play a senior technical leadership role on the ML team. Your responsibilities include hiring, mentoring, and developing other engineers; raising technical standards across reliability and operational excellence; and identifying where machine learning can create customer value. You will work on the full ML lifecycle: framing product problems with stakeholders, conducting exploratory data analysis, researching and selecting appropriate algorithms (from classic supervised models to transformer neural networks), performing offline evaluation, collaborating with engineers to productionize prototypes, and measuring real customer impact.
You will partner deeply with teammates and cross-functional stakeholders to build excellent ML products. The team has shipped everything from supervised models to unsupervised clustering to novel transformer applications, and you'll contribute to both cutting-edge research and pragmatic product delivery.
Required: 5–8 years of applied ML experience; previous background in a senior or staff role (data science, software development, or academia); demonstrated significant impact on products and teams; strong programming skills; experience as a primary technical leader; strong communication across engineering and disciplines; comfort with ambiguity; typically advanced education in ML or related field (MSc); scientific thinking.
Bonus: track record shipping ML products; PhD or research environment experience; deep expertise in NLP, deep learning, Bayesian methods, reinforcement learning, or clustering; strong stats/math background; data visualization and SQL skills.
