技术项目经理 - AI 数据处理
Technical Project Manager - AI Data Processing
技术项目经理 - AI 数据处理
工作模式：远程（覆盖 PST 时间段）- 基于 PST 时区
雇佣类型：全职（合同或正式雇佣）
关于 DATAmundi
DATAmundi 构建先进的软件解决方案，为我们的本地化和数据服务提供支持。我们通过交付高质量的数据集、验证流程和可扩展的数据处理方案，支持人工智能公司和研究团队。我们的研发工作探索如何通过结构化数据和验证方法对现代人工智能系统——包括大语言模型、语音模型和多模态系统——进行评估、改进和安全部署。
我们正在扩大研发活动，并寻求研究人员在人工智能生态系统中开展应用研究和技术推广合作。
关于该职位
我们正在招聘一位具备动手能力、数据工程技能的技术项目经理，以支持 AI 数据处理。你将把客户要求转化为可执行的验证逻辑，支持数据后处理，并帮助确保交付数据一致、可衡量，并符合客户指标和指南。
该职位位于技术交付、数据 QA 和自动化交叉领域。你将与开发团队紧密合作，并支持运营团队，同时编写/维护轻量级脚本和查询，将需求转化为质量保证检查。
你会做什么
· 负责数据交付的端到端协调，从接收、验证到交接。
· 与通过 S3 存储桶或直接上传的客户数据协作；确保正确的结构、完整性和下游使用的准备就绪。
· 将客户指南转化为自动化验证，使用 SQL、正则表达式和支持脚本。
· 创建并计算质量与一致性指标，例如：
· WER（词错误率），维护 Python 工具
· IAA（标注者间一致性）
· 根据需要创建其他数据集级别指标
· 使用 Windows 命令提示符进行批量文件操作（创建/移动/下载文件夹和文件），以支持处理和交付流程。
· 与内部开发团队合作，编写 Jira 工单以进行平台改进和错误修复（需求、复现步骤、验收标准）。
· 快速掌握内部平台和配置逻辑（例如，工作类型/模板），提供设置模式和权衡建议。
· 通过数据库工具查询数据集来调查问题，并生成清晰的发现总结和下一步计划。
查看英文原文
Technical Project Manager-AI DataProcessing
Work model: Remote (covering PST hours) - Based in PST timezone
Employment type: Full-time (Contract or Employment)
About DATAmundi
DATAmundi builds advanced software solutions that power our localization and data services. We support AI companies and research teams by delivering high-quality datasets, validation workflows, and scalable data processing. Our R&D initiatives explore how modern AI systems — including LLMs, speech models, and multimodal systems — can be evaluated, improved, and safely deployed through structured data and validation methodologies.
We are expanding our R&D activities and seeking researchers to collaborate on applied research and technical outreach within the AI ecosystem.
About the role
We’re hiring a Technical Project Manager with a hands-on, data engineering skillset to support Data Processing for AI.You’ll translate client requirements into executable validation logic for data processing workflows, support data post processing, and help ensure delivery data is consistent, measurable, and within client metrics and guidelines.
This role sits at the intersection of technical delivery, data QA, and automation. You’ll work closely with development teams and support the Operations Team while also writing/maintaining lightweight scripts and queries that turn requirements into quality assurance checks.
Whatyou’lldo
· Own the end-to-end coordination ofdata deliveries, from intake to validation and handoff.
· Work with clientdata delivered via S3 buckets or direct uploads; ensure correct structure, completeness, and readiness for downstream use.
· Translate client guidelines into automated validation using SQL, regex, and supporting scripts.
· Create and to compute quality and consistency metrics such as:
· WER (Word Error Rate)maintain Python utilities
· IAA (Inter-Annotator Agreement)
· Additional dataset-level metrics as required
· Use Windows Command Prompt for bulk file operations (creating/moving/downloading folders and files) to support processing and delivery workflows.
· Partner with internal development teams by writing Jira tickets for platform improvements and bug fixes (requirements, steps to reproduce, acceptance criteria).
· Quickly ramp on internal platforms and configuration logic (e.g., worktypes / templates), advising on setup patterns and tradeoffs.
· Investigate issues by querying datasets through database tools and producing clear summaries of findings and next steps.
Whatwe’relooking for
· 3 years experience in technical delivery / project coordination in a data environment (data, analytics, ML, QA automation, or platform operations.
· Practical comfort with:
· Python(scripting for metrics and data validation workflows)
· SQL (queries used in automated checks)
· Regex (pattern-based validation)
· Command line / Windows CMD (bulk file operations)
· Strong written communication and the ability to convert fuzzy requirements into precise, testable checks.
· Experience working with engineering teams and using tools like Jira to drive execution.
· Ability to evaluate options and recommend an approach based on pros/cons, timelines, and maintainability.
Nice to have
· Experience with speech/audio or text datasets (given WER and annotation agreement use cases).
· Familiarity with cloud data workflows (especially AWS S3 concepts like buckets, prefixes, access patterns).
· Experience with data labeling/annotation workflows and quality frameworks.
Salary: $60k-$85kOriginally posted on Himalayas