Maps Specialist (India) - DoorDash Dot

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, we want to talk to you! About the Role In this role, your main focus will be to work on a variety of QA and triage tasks to assist in the development of our autonomous delivery robot. A primary focus of the role will be to triage the logs of the daily testing runs of the robots conducted in the US. This includes replaying and analyzing specific events as annotated by the testing team, categorizing such events, and working with the software team to evaluate any required improvements. The role could also involve setting up various simulation scenarios for testing within our simulation environment as well as creating maps used by the autonomy stack for navigation. You’re excited about this opportunity because you will… Analyze: Utilize proprietary diagnostic tools and techniques to triage and diagnose robot autonomy issues accurately and efficiently Execute: Take charge of ensuring the prompt analysis of issues, generating reports and data visualizations that effectively prioritize and summarize identified issues Build: Develop and construct diverse scenarios within a simulation environment to test and validate new autonomy features. Additionally, create and maintain a library of scenarios to support comprehensive regression testing Collaborate: Work cross-functionally with Operations, Program Management, and Software Engineering teams to provide an effective feedback loop of identifying, routing, and monitoring key issues across various systems of the autonomy stack Optimize: Streamline and enhance QA processes and workflows Lead: Have opportunities to take end-to-end ownership of QA initiatives, encompassing process establishment, defining metrics, new team member training, execution, quality auditing, and rep

ABOUT THIS ROLE GHX connects healthcare suppliers and hospitals across North America, processing over 2.2 million Purchase Order (PO) documents per year through its ADM (Automated Document Management) platform. The platform processes the majority of documents automatically; documents the system cannot process with sufficient confidence are routed to a human review queue. The Document Review Specialist verifies those flagged documents and corrects extraction errors at the field level. Every correction feeds directly into model retraining — you are not maintaining a status quo, you are actively improving the platform’s accuracy over time. This is a precision operations role, not conventional data entry. KEY RESPONSIBILITIES Document Verification & Field Correction — 85% Verify documents like purchase orders, invoices, etc. flagged by the platform as requiring validation Compare extracted field values against the source document image and correct every discrepancy at the field level Verify and correct core fields, including vendor name, PO/Invoice number, line item descriptions, quantities, unit prices, delivery dates, and ship-to addresses Sustain throughput of ~30 documents per hour at a field accuracy rate of 99% or above Self-audit daily output before shift-end submission to catch and correct errors before they enter the system Flag ambiguous, damaged, or edge-case documents per the team escalation protocol; do not attempt to resolve documents outside defined parameters Process Documentation & Reporting — 10% Create and maintain Standard Operating Procedures (SOPs) for document review workflows, and update them as document types and field standards change Build and maintain process maps for end-to-end document review flows, including exception and escalation paths Perform basic analytics — collate production and quality data, and pull routine and ad-hoc reports on throughput, accuracy, and error trends as required Calibration & Continuous Improvement —

Opportunity Overview We're hiring a Data Architect who will serve as a senior technical leader responsible for architecting the complete lifecycle data moves, transforms, and creates value across every product line we operate. You'll own the blueprint for our enterprise data lakehouse - setting the standards, governance, and strategy that elevate data from a byproduct of operations to the company's most valuable asset. We need someone who pairs deep mathematical and logical modeling expertise with a builder's instinct - someone who codes, prototypes fast, and proves out next-generation AI data architectures before committing the organization to them. This role would need experience with US healthcare domain data. What You'll Do Semantic Layer Governance: Set the technical standard and reference architecture for a universal semantic layer across multiple distinct data products, ensuring unified definitions of complex metrics and healthcare business entities across Architect the Enterprise Context Layer: Define, scale, and govern the global Enterprise Ontology (abstract domain maps, business entity classes, and entity-relationship rules) that serves as the backbone for Agentic AI systems. AI-Native Prototyping : Leverage modern AI-native development environments (such as Cursor, GitHub Copilot) to rapidly generate, iterate, and document blueprints for complex enterprise data schemas and metadata layers. Security & Compliance Leadership : Embed regulatory compliance (HIPAA, FHIR) and security principles into platform design. Partner with security and compliance teams to ensure architectural decisions support audit readiness and risk mitigation. Cross-Functional Collaboration : Partner with executive leadership, product management, and engineering to translate business requirements into scalable technical solutions. Communicate complex architectural concepts to both technical and non-technical stakeholders. ISMS roles and responsibilities Good knowledge of Informati

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