AI Data Platform Product Manager – Annotation / Evaluation

Embedding VC

Product Manager for AI data platform focusing on data cleaning, annotation, quality, and evaluation processes. Collaborating with cross-functional teams to drive platform capabilities.

Posted 5/12/2026full-timePalo Alto • California • 🇺🇸 United StatesMid-LevelSeniorWebsite

About the role

Key responsibilities & impact

Own the design of the AI data platform product, supporting core processes such as data cleaning, annotation, quality control, evaluation, and dataset management.
Design annotation and evaluation features, including task configuration, workflow orchestration, review and quality checks, and result management.
Collaborate with the algorithms team to understand data requirements for model training and evaluation, and drive the establishment of data standards and quality mechanisms.
Drive the implementation of capabilities such as intelligent annotation, pre-annotation, and automated quality checks to improve data production efficiency.
Monitor data usage outcomes and drive bad-case feedback loops, data optimization, and model performance improvements.
Coordinate with algorithm, engineering, operations, and business teams to continuously iterate platform capabilities.

Requirements

What you’ll need

3+ years of product management experience; experience with data platforms, AI platforms, annotation platforms, or evaluation platforms is a plus.
Strong skills in process analysis and system design, with the ability to abstract complex business workflows.
Understanding of core processes such as data cleaning, annotation, quality control, evaluation, and dataset management.
Interest in or experience with large models, multimodal systems, agents, and intelligent annotation.
Strong data awareness and the ability to communicate effectively across teams.
Experience with B2B/platform products, task flow systems, or AI data-related projects is preferred.

Benefits

Comp & perks

Own the design of the AI data platform product, supporting core processes such as data cleaning, annotation, quality control, evaluation, and dataset management.
Design annotation and evaluation features, including task configuration, workflow orchestration, review and quality checks, and result management.
Collaborate with the algorithms team to understand data requirements for model training and evaluation, and drive the establishment of data standards and quality mechanisms.
Drive the implementation of capabilities such as intelligent annotation, pre-annotation, and automated quality checks to improve data production efficiency.
Monitor data usage outcomes and drive bad-case feedback loops, data optimization, and model performance improvements.
Coordinate with algorithm, engineering, operations, and business teams to continuously iterate platform capabilities.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data cleaningannotationquality controlevaluationdataset managementprocess analysissystem designdata optimizationmodel performance improvementintelligent annotation

Soft Skills

communicationcollaborationprocess abstractionteam coordinationfeedback managementproblem-solvingadaptabilitycritical thinkingorganizational skillsinterpersonal skills