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Embedding VC

Early-stage venture fund for Generative AI

Director of AI Product Management

Technical Product ManagementConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USANo salary listedIn-person

About the Job

Requirements

  • Eight or more years of product management experience, with significant experience in AI/ML-driven products, ad technology, or large-scale optimization platforms.
  • Demonstrated success shipping and scaling machine-learning-based systems across high-volume use cases.
  • Strong technical understanding of machine-learning fundamentals, including training pipelines, model evaluation, offline and online experimentation, feature engineering, reinforcement learning, and large language model workflows.
  • Proven leadership experience managing product management teams and influencing cross-functional executives.
  • Deep analytical mindset with fluency in data tools, metrics design, and scientific thinking.
  • Experience working in fast-paced software-as-a-service, retail media, or advertising technology environments.

Responsibilities

  • Define and own the multi-year AI strategy across optimization engines, agent frameworks, predictive models, attribution systems, and generative AI experiences.
  • Establish the vision and roadmap for AI-driven automation, intelligence, and decision-making across product surfaces.
  • Identify emerging AI opportunities, including large language models, agents, reinforcement learning, causal inference, marketing mix modeling, and multi-touch attribution, and convert them into product initiatives.
  • Lead, mentor, and scale a team of AI product managers, fostering excellence, critical thinking, and rapid iteration.
  • Build partnerships with Data Science, Machine Learning Engineering, Platform Engineering, go-to-market, and Customer Success teams.
  • Align executive stakeholders around strategy, roadmaps, and prioritization decisions.
  • Partner with AI and machine-learning leaders to define training data requirements, evaluation metrics, offline and online testing strategies, model deployment and monitoring standards, governance, explainability, and safe use.
  • Lead large-scale experimentation frameworks, including A/B tests, simulation, and offline replay.
  • Ensure continuous model improvement through robust feedback loops.
  • Design and drive the architecture of AI-driven bidding and budget optimization models, generative creative intelligence, multi-agent orchestration frameworks, spend forecasting and pacing engines, and advertiser guidance and insight-generation systems.
  • Work with machine-learning engineers and architects to ensure AI components are scalable, reliable, and explainable.
  • Communicate AI strategy, tradeoffs, and impact to executive leaders, technical teams, and customer-facing teams.
  • Serve as the executive-level voice of AI product across the organization.
  • Translate complex AI concepts into business and customer value narratives that guide go-to-market and operational decisions.
  • Ensure AI features are intuitive, trustworthy, configurable, and aligned with advertiser needs.
  • Guide UX and design on interfaces that express AI decisions transparently and empower users with control.
  • Drive adoption and measurable business outcomes across customer segments.

Desired Qualifications

  • Experience with Amazon Ads, demand-side platform bidding systems, marketing mix modeling, multi-touch attribution, predictive forecasting, or performance optimization models.
  • Experience deploying or integrating large language models, agentic systems, or generative AI into production workflows.
  • Mandarin proficiency for cross-regional collaboration.

About the Company

Embedding VC

Early-stage venture fund for Generative AI

Embedding VC is an early-stage venture fund that backs Generative AI startups. It provides seed to early-stage capital and operational guidance, leveraging a team of current and former builders and operators who can help portfolio companies grow. The fund’s approach centers on working closely with founders and using hands-on experience to scale AI projects, including those aiming toward AGI, during a period described as a new computing super cycle driven by AI innovations. Unlike funds that rely mainly on financial leverage, Embedding VC differentiates itself through its deep operator network, practical support, and focus on and commitment to building capable, scalable AI businesses. The overall goal is to support ambitious AI founders to advance the development and deployment of AI technologies and capture value in the expanding AI ecosystem.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Menlo Park, CA
Founded
2023

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