Senior Machine Learning Scientist

<div class="content-intro"><p><a href="https://fin.ai/">Fin</a>, now part of Salesforce, is on a mission to help businesses provide perfect customer experiences.</p> <p>Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system.</p> <p>Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI.</p> <p>Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce.</p></div><h2>What's the opportunity?&nbsp;</h2> <p>Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands.</p> <p>We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test.</p> <p>We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy.</p> <h2>What will I be doing?&nbsp;</h2> <ul> <li>Identify areas where ML can create value for our customers</li> <li>Identify the right ML framing of product problems</li> <li>Working with teammates and Product and Design stakeholders</li> <li>Conduct exploratory data analysis and research</li> <li>Deeply understand the problem area</li> <li>Research and identify the right algorithms and tools</li> <li>Being pragmatic, but innovating right to the cutting-edge when needed</li> <li>Perform offline evaluation to gather evidence an algorithm will work</li> <li>Work with engineers to bring prototypes to production</li>