Machine Learning Engineer

Key Skills

Database, Machine learning techniques, Node.js, NoSQL, Python Programming, PyTorch, SQL

Job Description

At Hearth, our mission is to radically expand our capacity to make sense of our networks. To empower teams to identify more mutuality and matched opportunities, we are building a network co-pilot that combines natural language interfaces with an elegant UI. Founded in 2022, Hearth envisions a new category of relationship-management led by AI that fundamentally augments our ability to focus on connection.

About Hearth

• Hearth's vision is AI that radically expands our capacity to act on our networks by making sense of the branching complexities of our relationships
• As an AI Chief of Staff, Hearth interacts with teams through a natural language interface and supports different network workflows
• We raised our seed from top Silicon Valley VCs
• Founded by Ashe Magalhaes (ML engineer in philanthropy, politics, tech)

About the Role

• Work directly with founders to drive implementation of long-term ML infrastructure
• Tackle unsolved AI research problems in relationship management
• Develop novel solutions for centralizing disparate network data, contact enrichment, and workflow recommendations
• Lead an engineering culture that is authentic, dynamic, and warm - as we grow, you'll have autonomy to stay an individual contributor or manage

You should

• Have meaningfully contributed to large-scale machine learning infrastructure projects
• Have experience in backend development and modeling integrations (ideally you are experienced in SQL/relational databases and NodeJS)
• Be a detail-oriented and opinionated engineer excited by rapid development cycles and building clean and documented applications

We're a small team of builders and artists based in New York City, united by a love of people, disciplined focus, fast execution, and the creative invitation to craft with skillful care. We believe talent is the ability to let ideas manifest themselves through you. We welcome the not knowing, the challenging tasks, the cyclic confrontation of ideas with real-world feedback. We're here to create.