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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in managing client engagements and data operations within AI/ML, focusing on data annotation and evaluation. Proficient in translating technical concepts for diverse stakeholders while ensuring project delivery meets quality metrics and acceptance criteria.
Highest-signal resume keywords
Technical Program ManagementData AnnotationClient ManagementAnalytical SkillsPython
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data OperationsDataset EvaluationQuality MetricsAcceptance CriteriaAI/ML WorkflowsModel EvaluationBenchmarkingData ProductionSQLAnalytics/BI Tools
Soft Skills
Attention to DetailCommunicationRisk ManagementCross-Functional Team ManagementProblem Solving
Tools & Technologies
Annotation PlatformsBenchmark/Eval FrameworksRLHF Workflows
Certifications & Qualifications
PMPAgile
Industry Keywords
AI/MLData ScienceTechnical Program ManagementData Annotation
Tech Stack
Tools & technologiesPMPPythonSQL
About the role
Key responsibilities & impact- Own assigned client engagements from kickoff through completion
- Build and manage human data, including data annotation, labeling, and evaluation datasets, for off-the-shelf AI/ML products
- Coordinate data operations, analysts, and subject-matter experts to keep projects on track
- Translate technical concepts for non-technical stakeholders and vice versa
- Balance priorities across multiple clients and projects, proactively identifying and resolving risks
- Use quality metrics, acceptance criteria, and dataset-level analysis to identify gaps and drive improvements
- Contribute to process and delivery improvements beyond day-to-day execution as bandwidth allows
Requirements
What you’ll need- 4+ years of experience in technical program/project management, delivery management, or data operations within AI/ML, data annotation, or related technology domains
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field
- Experience working in technical settings (does not require a deeply technical background)
- Demonstrated ability to manage and influence cross-functional teams without direct authority; potential to build and lead a team as the practice scales
- Strong attention to detail with a track record of owning client-facing deliverables to exacting specifications
- Strong analytical skills — comfortable working with quality metrics, acceptance criteria, and dataset-level analysis
- Excellent client management, communication, and risk management skills
- Understanding of LLMs, model evaluation, benchmarking, data annotation, and AI/ML data production workflows
- Experience delivering datasets or evaluation assets to AI labs, research organizations, or ML engineering teams
- Exposure to benchmark/eval frameworks, annotation platforms, SME-driven data production, or RLHF/human-feedback workflows
- Working knowledge of Python, SQL, or analytics/BI tools for dataset inspection and metrics reporting
- PMP, Agile, or equivalent program management certification