# Data Operations Manager

**Company:** [Origin](https://hotfix.jobs/companies/origin-tech)
**Location:** Bengaluru, India
**Role:** Data Engineering
**Experience:** 2+ years
**Skills:** Data Operations, Data Annotation, Data Collection, Machine Learning Operations, Computer Vision, Robotics, Python, SQL, Video Annotation, 3D Point Clouds, Segmentation, Object Tracking, Annotation Platforms, Data Quality Metrics, Privacy Controls
**Posted:** 2026-08-24

> Leads the operational engine for collecting and annotating real-world and simulated data used by perception and robot-learning teams. The role manages vendors and annotators, quality systems, dataset governance, dashboards, and cross-functional delivery.

## Job Description

## Responsibilities
- Convert perception and robot-learning requirements into data collection plans, annotation ontologies, instructions, examples, and acceptance criteria.
- Coordinate external agencies and in-house robot testing teams for curated data collection.
- Build, train, and manage internal annotators and external vendors; track throughput, quality, and cost.
- Design sampling, review, adjudication, gold-set, inter-annotator agreement, and audit processes.
- Maintain dataset versions, metadata, provenance, consent and usage records, and engineering handoffs.
- Partner with ML engineers to diagnose model failures and prioritize high-value data.
- Build dashboards for coverage, quality, turnaround time, backlog, rework, and unit economics.
- Protect sensitive customer and site data through access, retention, and handling processes.

## Requirements
- 2+ years in data operations, annotation, data collection, ML operations, quality operations, or related program management.
- 2+ years managing external agencies and stakeholders.
- Experience leading people or vendors and delivering large, quality-controlled datasets on schedule.
- Experience mentoring and training junior staff.
- Ability to write precise annotation guidelines and translate ambiguous technical needs into repeatable workflows.
- Comfort with spreadsheets, dashboards, issue trackers, and data-quality metrics.
- Strong analytical judgment, attention to detail, and cross-functional communication.
- Bachelor’s degree or equivalent practical experience in engineering, data, operations, or a related field.

## Nice-to-haves
- Experience with computer vision, robotics, autonomous vehicles, mapping, speech, multimodal data, or sensor-rich ML products.
- Experience with teleoperation or embodied-AI data collection, video annotation, 3D point clouds, segmentation, tracking, or key-point labeling.
- Familiarity with Python, SQL, annotation platforms, privacy controls, and vendor contracting.

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