Annotation Program Manager
Gather AI
| Company | Gather AI |
| Category | Data & Analytics |
| Location | Remote (India) |
| Remote | Remote |
| Employment | Not stated |
| Level | Manager |
| Salary | Not stated by the employer |
| Posted | 16 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Annotation Program Manager
About Us
Are you ready to build the future of supply chain? At Gather AI, we're not just creating software, we're pioneering a new era of warehouse intelligence. We've developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining "on-time, in full" delivery.
If you're looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We're leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.
About the Team
Our engineering organization spans autonomy, computer vision and machine learning, embedded and hardware systems, full-stack, and cloud, all working in parallel across multiple active product lines tied to live customer deployments. It's a technically deep, fast-moving team where individual contributors carry real accountability and the work shows up directly in customer operations. We're at the stage where the complexity of running concurrent programs across disciplines has outpaced informal coordination, and we're ready to fix that.
About the Role
We are looking for an experienced Annotation Program Manager to own and scale our production annotation operations supporting computer vision and machine learning initiatives. This role is responsible for managing external annotation partners, improving annotation quality, maintaining documentation, and ensuring high-quality labeled datasets are delivered on schedule to support model development.
You will work closely with Machine Learning Engineers, Data Engineers, and Operations teams while serving as the primary owner of our annotation programs and vendor relationship. Success in this role requires a combination of technical problem-solving, operational excellence, and strong project management.
What You'll Do
Own day-to-day management of our annotation vendor relationship, including workload planning, throughput monitoring, and SLA management.
Coordinate annotation batches, scheduling, and delivery timelines across multiple production programs.
Monitor annotation quality and continuously improve labeling accuracy through structured QA processes.
Develop, maintain, and improve annotation SOPs, taxonomies, and documentation.
Build and maintain Python-based workflows for annotation data preparation, API integrations, reporting, and validation.
Partner with ML teams to prioritize annotation work that maximizes model performance.
Track work across Jira and communicate project status, risks, and capacity needs to stakeholders.
Drive operational improvements that reduce annotation turnaround time while maintaining high quality.
First 90 Days
Within your first three months, you will be expected to:
Own Annotation Operations
Take over day-to-day coordination with CloudFactory from existing program owners.
Own weekly turnaround time (TAT) reporting, batch scheduling, and vendor escalation management.
Become the primary operational contact for annotation delivery.
Become Fluent in Existing Annotation Programs
Develop working expertise in both active production annotation programs:
MHEV forklift event labeling (PICK_UP / DROP_OFF) using the internal MHEV annotation application
Drone Human-in-the-Loop (HIL) annotation pipeline supporting case counting and empty detection through the CloudFactory API
Improve Annotation Quality
Audit completed annotation batches across both programs.
Run inter-annotator agreement (IAA) analysis against gold-set datasets.
Identify common annotation errors and present recommendations to ML leads.
Le
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