Data Collection

<p><strong>About Hark</strong></p> <p>Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory.</p> <p>We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world.</p> <p>To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems.</p> <p><strong>About the Role</strong></p> <p>You'll own data collection at Hark — the programs, the vendors, and the pipelines that turn raw signal into training data our models can actually learn from.</p> <p>That means running end-to-end campaigns across human feedback, synthetic data, and product-embedded signals. The quality of what we collect shapes the quality of what we ship, and this role owns that loop.</p> <p>This is a high-ownership role on a small team. You'll work directly with researchers, engineers, and external partners, and the data you deliver will directly influence how our models behave in the real world.</p> <p><strong>Responsibilities</strong></p> <ul> <li>Design and run data collection programs end-to-end — scoping requirements, writing instructions, defining success criteria, and driving execution with vendors and annotators.</li> <li>Manage external vendor relationships. Be the primary interface between Hark and data partners, keeping quality high and timelines on track.</li> <li>Assess collected data using internal tooling, identify quality issues, and feed clear, actionable feedback back to vendors and annotators.</li> <li>Collaborate closely with model researchers and engineers to understand what data is needed, translate that into operational plans, and deliver.</li> <li>Track program metrics, surface insights, and drive continuous improvements to quality, throughput, and process.</li> <li>Identify gaps in tooling and workflows and propose concrete improvements.</li> </ul> <p><strong>Requirements</strong></p> <ul> <li>Operational excellence. You can manage multiple programs simultaneously, keep track of details under pressure, and bring structure to fast-moving situations.</li> <li>Experience working with external vendors or contractors. You know how to set expectations, manage relationships, and hold partners accountable to quality.</li> <li>A knack for data. You've gone beyond surface-level metrics — you dig in, find patterns, and use what you find to make things better.</li> <li>Strong communication. You can translate between research requirements and operational reality, and you keep everyone aligned without letting things slip.</li> <li>Comfort with ambiguity and fast iteration. You take a rough problem, build a process around it, get feedback, and tighten it quickly.</li> <li>Genuine curiosity about AI. You don't need to be an ML researcher, but you care about how models learn and why data quality matters.</li> <li>2+ years of relevant experience in data operations, program management, or a related field.</li> </ul> <p><strong>Bonus Qualifications</strong></p> <ul> <li>Experience managing human feedback or preference data programs.</li> <li>Familiarity with data annotation platforms or labeling pipelines.</li> <li>Experience with synthetic data generation or evaluation dataset design.</li> <li>Background working at a fast-moving AI or research-driven company.</li> </ul> <p><strong>Compensation</strong></p> <p><span data-sheets-root="1">The US base salary range for this full-time position is between $150,000 - $250,000 annually.</span></p> <p>The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.</p>