Strategic Projects Associate, Safety

Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.

In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month.

Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale.

As a Safety Strategic Projects Associate (SPA), you will own the execution of large-scale human data programs that directly power frontier AI model training and evaluation. You will design, build, and execute operational workflows supporting model policy annotation and develop evaluations across a range of policy areas. You will use model policy annotation to help inform model training, evaluation, and enforcement decisions across leading AI systems.

Working hands-on with leading AI labs and technology companies, you will make real-time decisions that affect revenue, margins, delivery quality, and long-term customer relationships. This is a high-ownership, outcomes-driven role for operators who thrive in ambiguity, move fast with incomplete information, and are accountable for results at scale.

What you'll do:

• Support the design and iteration of annotation frameworks and labeling workflows that scale while maintaining precision, accuracy, and inter-rater agreement

• Coordinate trusted annotators and contribute to a culture of consistency, care, and sound judgment when handling sensitive content and complex edge cases

• Partner with policy leads to organize and surface insights on policy gaps, classification ambiguities, and nuanced scenarios identified through annotation work

• Build and maintain detailed annotation playbooks, quality resources, and auditor guidance across diverse datasets and regulatory domains

• Analyze annotation data to identify emerging trends, systemic labeling errors, and opportunities to strengthen internal safety policies

• Work with frontier AI labs and internal stakeholders to support project scoping, issue resolution, and delivery of model policy programs

• A strong academic record as a recent graduate (or someone graduating soon), ideally with internship or light work experience in trust and safety, policy enforcement, regulatory compliance, risk management, management consulting, government, or a related field

• Strong analytical and first-principles problem-solving skills; comfort or aptitude for drawing insights from large datasets (SQL proficiency a plus)

• Excellent written and verbal communication skills, including the ability to work effectively with senior stakeholders and customers

• High ownership and a reliable, detail-oriented approach to execution

• Curiosity and an ability to quickly learn technical AI concepts and industry trends

• STEM background or exposure to technical concepts (e.g., data, software, or AI)

• Experience supporting policy enforcement or content-review workflows across large, distributed workforces

• Familiarity with high-severity policy harms, including violent activities, dangerous organizations or individuals, or sexual activities

• Experience developing evaluations for harmful-content or policy-enforcement use cases

Note: This role involves exposure to sensitive or explicit content (e.g., violent, sexual, or otherwise disturbing material) as part of safety and policy evaluation work.