Technical Project Manager
New
Remote, MXFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 4 plus years of experience
- Required Skills
- Project ManagementSQLArtificial IntelligenceData AnalysisMachine LearningMicrosoft ExcelRisk Management
Requirements
- 4 plus years of experience in project management, technical operations, or AI and ML data programs, ideally in high volume data operations.
- Proven ability to manage multiple projects while upholding high delivery and quality standards.
- Familiarity with large language models or generative AI, with experience in data annotation or AI training data projects strongly preferred.
- Strong planning, organization, and stakeholder communication capability across technical and non-technical audiences.
- Demonstrated risk management and forecasting discipline within project environments.
- Strong data orientation, with the ability to interpret dashboards, identify bottlenecks, and make operational decisions based on metrics.
- Working knowledge of tools such as Excel or SQL, with basic coding or data skills preferred.
- Project Management qualification (ideally from Project Management Professional PMP) or Udemy, Coursera or Google certification
- Bachelor’s degree in a related field such as Economics, Business, Computer Science, Linguistics, Engineering, or Data Science (nice to have)
Responsibilities
- Lead planning and execution of GenAI projects, ensuring clear scope, timelines, execution, and deliverables while maintaining client relationships.
- Deliver projects on time and to defined quality benchmarks through disciplined operational management.
- Drive accurate forecasting and proactive risk mitigation to protect delivery commitments.
- Align internal teams, contributors, and clients to ensure clarity of expectations and execution standards.
- Strategically improve productivity and quality by identifying bottlenecks and applying data driven operational decisions.
- Strengthen stakeholder engagement through structured communication and transparent daily, weekly, and monthly reporting.
- Establish structured project closure practices, capturing lessons learned, iterating operating processes, and identifying future opportunities.
- Drive thought leadership and increase scalability of delivery models by applying repeatable workflows and structured improvements to accelerate delivery while maintaining quality.
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