Product Marketing Lead, GenAI

Responsibilities

• Own positioning and messaging for Scale’s GenAI data products, articulating our differentiation on data quality, delivery speed, and multimodal breadth in a way that resonates with AI researchers and technical buyers.
• Lead the content and social strategy for Scale Labs’ dedicated online presence, taking a research-native approach that earns attention and credibility from the AI community.
• Build and maintain competitive intelligence and a sharp point of view on the data market, arming the team with differentiated positioning as the market evolves.
• Partner with Scale Labs researchers to amplify published work - leaderboards, benchmarks, and research papers - and translate it into pipeline and demand generation for the GenAI business.
• Develop go-to-market strategies for new data offerings and modalities, working closely with product and sales to drive awareness and build market momentum.
• Collaborate cross-functionally with sales, engineering, and research to ensure consistent, compelling messaging across every customer touchpoint.

Requirements

• 5+ years of experience in product marketing, with a track record of marketing technical products to developer or research audiences.
• Strong technical fluency and passion for AI. You can hold a credible conversation about AI/ML fundamentals, training, and the role of data quality in model performance.
• Experience building social-native content and community strategies on platforms like X, with an instinct for what resonates with technical practitioners.
• Excellent written communication and storytelling skills — you can make complex technical concepts compelling without oversimplifying them.
• Ability to work across functions and move fast in a dynamic, high-stakes environment.

Nice to Haves

• Familiarity with the AI training data market, or adjacent data and infrastructure spaces.
• An existing network or relationships within the AI research community.
• Experience navigating competitive markets where differentiation requires more than feature comparisons.