Head of Annotation Operations

Obvio•San Carlos, CA

About The Position

Each year, more than 7,500 pedestrians are killed by drivers in the U.S.—a number that has increased by 70% over the past decade. Despite growing awareness, most cities still struggle to curb dangerous driving. “Vision Zero” efforts across the country are falling short. Obvio AI exists to change that. We deploy solar-powered, AI-assisted cameras to enforce traffic laws where pedestrians are most vulnerable—automating enforcement in ways that police departments or traditional systems cannot. Our approach has already led to a dramatic reduction in reckless driving and improved safety for pedestrians, drivers, and law enforcement alike. Founded by the team behind Motive’s AI dashcam, Obvio is backed by Bain Capital Ventures and Khosla Ventures. We recently raised a $22M Series A and are working with some of the most forward-thinking cities in the country. With meaningful revenue, a massive market, and strong policy momentum, we’re building the intelligence layer for safer streets globally. About the Role Obvio’s enforcement system depends on accurate, consistent, and auditable human review. We are hiring a Head of Annotation Operations to own our annotation and review function end-to-end as we scale. This role will lead a team that will substantially grow over the next year. You will design and operate the workflows, quality systems, training programs, and performance management needed to run a high‑throughput, safety‑ and compliance‑critical operation.

Requirements

7+ years in operations leadership, program management, or process‑heavy environments (e.g., trust & safety, compliance ops, fraud, payments, BPO, customer support ops, or data labeling).
3+ years managing people, including building lead or manager layers.
Proven experience scaling teams and workflows while improving quality and reliability.
Strong process design skills with the ability to turn ambiguity into clear SOPs and measurable outcomes.
Excellent written communication skills, especially for guidelines and edge‑case documentation.
Data‑driven operator comfortable using metrics and dashboards to run the business.
High ownership mentality with accountability for outcomes.
Calm and structured in high‑stakes, fast‑moving environments.
Collaborative and effective across operations, engineering, and leadership.
Bias toward action and continuous improvement.

Nice To Haves

Experience in regulated or compliance‑sensitive review workflows requiring auditability.
Familiarity with inter‑annotator agreement, calibration design, and statistical QA methods.
Experience with annotation or review tooling (commercial or custom).
Background in enforcement‑adjacent, public sector, or safety‑critical operations.
Startup experience building systems from first principles.

Responsibilities

Own execution and continuous improvement of Obvio’s annotation and review workflows for automated traffic enforcement.
Translate enforcement requirements and edge cases into clear reviewer guidelines, task specs, and escalation paths.
Balance throughput, accuracy, and consistency in a high-stakes operational environment.
Design the operating model for a rapidly scaling review organization, including team structure, lead roles, and QA functions.
Lead hiring, onboarding, and ramp programs to ensure reviewers reach proficiency quickly.
Build and run performance management systems including coaching, feedback, and accountability.
Define and maintain rubrics, golden datasets, calibration packs, and edge‑case decision trees.
Implement QA systems such as sampling, double review, adjudication, and calibration sessions.
Reduce quality escapes and build preventative controls for high-risk review categories.
Ensure documentation, version control, and audit readiness across all annotation workflows.
Own forecasting, staffing models, and capacity planning tied to volume growth and city deployments.
Build dashboards and operating reviews covering accuracy, agreement, throughput, backlog, rework, cost, and SLA adherence.
Identify bottlenecks and execute improvements across people, process, and tooling.
Partner closely with Product, Engineering, and ML to improve reviewer tooling, automation, and queueing logic.
Establish human‑in‑the‑loop feedback loops that improve model performance and reduce reviewer burden over time.
Ensure secure and auditable operational workflows.
Serve as the primary owner for annotation operations with leadership and cross‑functional partners.
Provide clear, regular updates on status, quality trends, risks, and mitigation plans.
Build scalable playbooks and documentation as the organization grows.