Your impact
At Handshake, Machine Learning is at the heart of our mission to democratize access to opportunity. Every student deserves to be seen, not just by any employer, but by the right one. In a three-sided marketplace spanning students, employers, and educators, machine learning is how we personalize discovery, match intent with opportunity, and drive better outcomes at scale.
As Director of Engineering for Machine Learning, you’ll lead the team responsible for shaping our marketplace’s intelligence and delivering experiences that feel intuitive, relevant, and uniquely valuable to each user. This is a critical leadership role with wide-ranging impact, overseeing the technical vision, organizational health, and cross-functional partnership required to build the future of AI at Handshake.
From rethinking how students are matched to jobs, to optimizing employer pipelines, to evolving our ML platforms for the AI economy, you’ll be at the helm of both strategic innovation and deep execution. It’s an opportunity to lead during a time of transformation, rebuild and grow a high-potential team, and ensure our AI efforts serve real human outcomes.
Your role
Define and drive the ML strategy that powers relevance, personalization, and marketplace efficiency across all sides of Handshake’s platform.
Lead and coach an organization of ML Engineers and Software Engineers, including Staff Engineers and Engineering Managers, through a period of rebuilding and growth.
Partner closely with Product, Data Science, and Design to identify high-leverage opportunities to embed intelligence into user experiences.
Establish and scale best-in-class ML development practices from experimentation and evaluation to deployment and monitoring.
Champion a healthy, resilient engineering culture rooted in mentorship, technical excellence, and a clear sense of purpose.
Bring an opinionated lens to the role of Gen AI and Agentic Experiences in the future of talent and help Handshake build toward it with integrity and ambition.
Your experience
Deep expertise in applied machine learning and AI, ideally in multi-sided marketplaces or recommendation systems.
Proven leadership experience managing engineering teams at scale, including people managers and senior ICs.
A track record of shipping impactful ML/AI products and platforms, with clear metrics and end-user impact.
A strong coaching mindset and the ability to rebuild, scale, and energize high-performing teams through change.
Product and strategic intuition: you know when to go deep, when to pivot, and how to connect technical work to business and user outcomes.
Exceptional communication and collaboration skills—you bring clarity and energy across cross-functional teams.
A commitment to diversity, equity, and inclusion, and a belief in building teams where every engineer can thrive.
Bonus areas of expertise
Familiarity with foundational models, vector search, or retrieval-augmented generation (RAG) techniques.
Experience operating in regulated or international markets with complex user dynamics.