# Data Operations Manager **Company:** [Origin](http://jobs.workable.com/companies/i6CRnMYNgc1yzpDvadsnAg.md) **Location:** Bengaluru, India **Workplace:** on site **Department:** Operations [Apply for this job](http://jobs.workable.com/view/46caadb1-a141-48b1-91d7-be87fe85d972) ## Description About Origin Origin (previously 10xConstruction) is building general-purpose autonomous robots for US construction to tackle rising costs, safety risks, and labour shortages. Our modular, multi-trade platform combines purpose-built hardware with real-time site intelligence to navigate complex environments and execute tasks with precision. Trained in high-fidelity simulation and already deployed on live sites, our robots deliver faster execution, stronger project economics, and meaningful cost savings. Join India’s talent-dense robotics team, with colleagues from IITs, Stanford, UCLA, and other leading institutions. About the role As Data Annotation and Collection Manager, you will build the operations engine that supplies high-quality real-world and simulated data to Origin’s perception and robot-learning teams. You will own collection protocols, annotation specifications, workforce and vendor execution, quality controls, data lineage, and delivery schedules. The role requires a strong blend of operational leadership, analytical rigour, and enough technical understanding to translate model needs into reliable datasets. Key responsibilities \- Convert perception and robot-learning requirements into clear data collection plans, annotation ontologies, instructions, examples, and acceptance criteria. \- Plan and coordinate with external agencies and inhouse robot testing team for curated data collections based on inputs received from requesting team. \- Build, train, and manage internal annotators and external vendors; allocate work and 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 handoffs to engineering. \- Partner with ML engineers to diagnose model failures and prioritise the next highest-value data. \- Build dashboards for coverage, quality, turnaround time, backlog, rework, and unit economics. \- Protect sensitive customer and site data through clear access, retention, and handling processes. ## Requirements Required qualifications and skills \- 2+ years in data operations, annotation, data collection, ML operations, quality operations, or a related program-management role. \- 2+ years in managing external agencies and stakeholders. \- Experience leading people or vendors and delivering large, quality-controlled datasets on schedule. \- Mentored and trained junior staff to build a strong team. \- Strong ability to write precise annotation guidelines and convert ambiguous technical needs into repeatable workflows. \- Comfort with spreadsheets, dashboards, issue trackers, and data-quality metrics. \- Strong analytical judgement, attention to detail, and cross-functional communication. \- Bachelor’s degree or equivalent practical experience in engineering, data, operations, or a related field. Preferred experience \- Computer vision, robotics, autonomous vehicles, mapping, speech, multimodal data, or other sensor-rich ML products. \- Teleoperation or embodied-AI data collection, video annotation, 3D point clouds, segmentation, tracking, or key-point labelling. \- Familiarity with Python, SQL, annotation platforms, privacy controls, and vendor contracting.