Jobs at Handshake

Source, pitch, negotiate, and close enterprise data partnerships that supply proprietary datasets to frontier AI labs. Manage end-to-end deals, translate technical data requirements, structure commercial and compliance terms, maintain C-suite relationships, and partner with engineering and legal to deliver compliant, recurring licensed data.

Lead design and build of large-scale data infrastructure, evaluation systems, and developer tooling for AI coding models. Architect scalable data pipelines, execution environments, and backend services; improve reliability and observability; partner with ML researchers; mentor engineers and drive reusable platform standards.

High-volume sourcing and initial screening for the Handshake AI Fellowship. Own top-of-funnel sourcing, engage passive technical/STEM candidates, provide market insights, track recruiting metrics in Ashby, and hand off qualified candidates to project teams.

Lead a team bridging frontier AI research and enterprise delivery to design post-training and RL environments, scale post-training infrastructure, support strategic lab projects, manage client relationships, and grow engineering and research talent while shaping technical roadmap.

Build and ship growth-focused experiments across onboarding, activation, retention and notifications. Architect and scale distributed backend systems for millions of users, collaborate with PMs and data scientists, mentor engineers, and balance rapid iteration with production-grade durability.

Lead two engineering teams (Quality and Annotations) totaling ~15 engineers to build AI quality/evaluation tooling and an annotations platform. Own operator workflows, tasking flows, and pipeline infrastructure, develop senior ICs and EMs, set cross-team technical strategy, and partner with stakeholders to prioritize platform investments that accelerate data delivery and model evaluation.

Own end-to-end relationships for $100M+ frontier AI lab accounts, translating ambiguous goals into clear priorities, partnering with delivery teams, making high-judgment tradeoffs, driving expansion and renewal, and defining KPIs and SLAs to ensure customer and leadership alignment.

The Staff Forward Deployed Engineer will define technical strategies, oversee deployments for strategic clients, and mentor engineers while enhancing engineering practices.

The Senior Forward Deployed Engineer will lead deployment solutions, mentor other engineers, and enhance customer engagement through technical leadership and innovative problem-solving.

Source, pitch, negotiate, and close enterprise data licensing partnerships for Handshake AI. Translate research requirements into partner profiles, structure commercial and privacy-compliant terms, manage C-suite relationships through long sales cycles, and coordinate with engineering and data teams to deliver signed datasets. Forecast and report pipeline and closed deals.

Own a portfolio of education partners to drive retention, renewals, and expansion. Build engagement programs and trainings, monitor usage and health signals, and coordinate cross-functionally to resolve partner needs. Travel 25–35% and act as strategic advisor and customer advocate to improve adoption and long-term outcomes.

Design, build, evaluate, and deploy ML systems for search, recommendations, embeddings, and personalization. Work with large datasets to create features, train models, run experiments, monitor production models, and improve reliability, latency, and marketplace outcomes in collaboration with cross-functional partners.

The Engagement Management Lead will drive customer relationships by managing the full engagement lifecycle, ensuring successful implementation, and translating customer needs into actionable programs.

As a Machine Learning Engineer I, you will develop and deploy machine learning systems for core relevance signals, collaborating with engineers and product teams.

Manage a team of Strategic Project Leads in delivering high-stakes AI data projects while ensuring operational excellence and performance metrics.

Build AI-driven workflows, automations, and agents for GTM teams; mine and score prospect signals; implement and maintain Salesforce- and warehouse-integrated systems using Python, SQL, BigQuery, Clay, and orchestration tools; own end-to-end delivery, monitoring, and documentation.

Lead and scale a Growth Engineering team owning acquisition, activation, retention, and notification systems. Build a modular, extensible growth platform for experimentation and personalization, drive architecture and technical strategy, partner with Product/Data/Marketing, raise engineering quality and observability, hire and develop leaders, and deliver high-impact growth outcomes.

Build and maintain Reinforcement Learning Environments platform: implement backend features and frontend interfaces, support data pipelines for model training, improve system reliability and performance, and collaborate with senior engineers to deliver modular workflow domains.

Build and operate shared ML/AI infrastructure: data pipelines, feature stores, training, model serving and LLM platform work. Scale inference and training (GPU, batching, autoscaling), enable evaluation and post-training workflows, and partner with AI, data science, and product teams to productionize models and improve platform reliability and developer experience.

Lead product analytics for Handshake's recruiting marketplace: define metrics, own analytics strategy, run experiments, evaluate ML models, perform cohort and funnel analyses, build dashboards, and partner with product, engineering, and analytics engineering to drive data-informed growth and pricing decisions.