AltaML

• Review and enter structured data from documents and raw sources into our platform, including equipment service manuals, technical specifications, parts information, and operator guides. • Apply equipment domain knowledge to validate that data entries are technically accurate, contextually correct, and consistent with how equipment is actually used in the field. • Assign metadata, categories, and keywords to improve searchability, consistency, and usability across the product. • Verify that AI-generated or system-produced answers, recommendations, and outputs are accurate, complete, and aligned with the source documentation — flagging anything misleading, incomplete, or technically incorrect. • Add contextual notes, corrections, or clarifications to improve the accuracy and usefulness of product responses. • Identify patterns, errors, or gaps in equipment data and escalate appropriately to ensure nothing falls through the cracks. • Serve as a domain-informed reviewer of product outputs, ensuring that answers, search results, and recommendations reflect real-world equipment knowledge and not just surface-level pattern matching. • Cross-reference product responses against source materials (service manuals, OEM documentation, technical bulletins) to confirm factual accuracy. • Develop and maintain a working understanding of common equipment failure modes, maintenance procedures, and service workflows to better evaluate the quality of product outputs. • Proactively identify cases where the product is producing answers that are technically plausible but incorrect, incomplete, or missing important safety or procedural context. • Contribute to building internal QA checklists, rubrics, and benchmarks for evaluating answer quality over time. • Work closely with external partners to communicate requirements, provide clarifications, and ensure alignment with internal standards. • Help manage work queues, assign tasks (internally or externally), and track progress against deadlines. • Review partner outputs with a critical eye for both process compliance and equipment accuracy, providing structured feedback and collaborating to continuously improve quality. • Help define, document, and refine data entry guidelines, workflows, and standard operating procedures — including equipment-specific guidelines for how technical content should be structured and reviewed. • Identify inefficiencies in data processing workflows and recommend improvements. • Track key metrics (accuracy rates, quality scores, throughput, turnaround time) and provide regular updates to stakeholders.

• Take real-world equipment manuals, documents, and raw data and help turn them into clean, organized, and usable information. • Work with outside partners and help keep projects moving, making sure everyone is aligned and getting quality work done on time. • Review equipment manuals and documents, tagging key details (like publication date, part number, models applicable, etc..) so they’re easy to find and use later. • Add categories, keywords, and structure—like sorting tools into the right drawer—so data is consistent and searchable. • Double-check work to make sure everything is accurate and meets standards. • Add helpful notes or clarifications to improve understanding for others down the line. • Spot anything unusual, incorrect, or worth flagging. • Work with outside teams doing similar work—answer questions, give direction, and make sure their output meets expectations. • Help organize the workload, assign tasks, and keep things moving toward deadlines. • Review completed work, give clear feedback, and help improve processes over time. • Help build and improve step-by-step processes so work is consistent and repeatable. • Look for ways to make tasks faster, smoother, and more efficient. • Track progress (quality, speed, volume) and share updates with the team.