Moloco Jobs (NOW HIRING)

Moloco is an AI-native company. We built our reputation on outcome-based advertising powered by deep learning, and we are now democratizing that capability for commerce: putting the same caliber of ML that the largest technology companies built for themselves into the hands of retailers, marketplaces, and commerce platforms. Moloco Commerce Media (MCM) is where that happens. Some of the world's largest commerce platforms run their advertising business on MCM, using our AI to improve what shoppers see and grow their ad revenue at the same time.

Retail media is the fastest-growing channel in advertising, and most retailers still compete on ad load and CPC floors. We think the frontier problem is somewhere else. Ad quality and performance, meaning relevance, ranking, bidding, and measurement, is what actually decides whether an ad works. Getting it right means reasoning about shopper intent, item relevance, and advertiser economics simultaneously, across billions of decisions a day. It is a hard AI problem, and it is largely unsolved across this industry.

As Director of Product Management for Ads Quality and Performance, you set the strategy for the domain and are accountable for what it delivers: our customers' ad businesses growing past the ceiling that weak relevance, blunt targeting, and unclear attribution impose on them. You will work alongside our ML, bidding, and data science teams, hold the whole picture across retrieval, scoring, bidding, pacing, and measurement, and define what best-in-class looks like in commerce. You will start as the senior individual owner of this domain, with the mandate and the support to build a team around it as the work scales. This role reports to the Head of Product, Moloco Commerce Media.

You will work across MCM's most technical teams: ML and applied science, bidding, and data science. Your job is turning frontier ML and bidding optimization capabilities into products that perform at commerce scale.

• Own the ads quality and performance product roadmap, and deliver results. Translate advertiser and platform problems into ML, bidding, and quality problems. Decide what the system optimizes for and why, so the roadmap targets the business outcome rather than the metric that is easiest to move.
• Ship performance controls that empower our customers. Turn manual, often one-off technical capabilities and implementations into scalable product solutions.
• Make difficult trade-offs. Relevance against revenue. Advertiser value against platform yield. Short-term lift against long-term trust. These get debated and decided in your forum, with evidence.
• Move complex problems across customer, technical, and organizational lines. In addition to closely partnering with our engineering teams, you will work directly with our customer-facing teams and engage our customers' data science and ad operations leaders.
• Learn how AI and advanced modeling deliver relevant, high-performing commerce ads for the largest retailers in the world. What it takes to build state-of-the-art commerce models alongside the retailers themselves, and prove them against live demand. How a breakthrough for one retailer becomes a capability every retailer can deploy. Where new technology retires ad business growth constraints the legacy ad stack couldn't break through.

• 10+ years in product management, with a track record of owning a domain end to end, from strategy through shipped, measured outcomes. You are ready to operate as the senior individual owner first, and you want to build and lead a team as the area grows.
• Depth in ads quality, ML-driven ranking, bidding, or recommender systems. Large-scale ads ranking, adtech, and commerce search and recommendation are the most direct backgrounds.
• Enough technical fluency to earn credibility with ML and data science teams: you help shape the problem framing and stakeholder translation, and contribute points of view on system direction and product implications.
• Rigor on measurement. You can define outcome metrics and keep proxy metrics from quietly becoming the goal.
• Executive communication and the standing to move senior stakeholders across product, engineering, and customer teams.

• PM with deep experience embedded in an ML, ranking, or recommendations team.
• Commerce or marketplace advertising exposure, including familiarity with retrieval, auction mechanics, pacing, conquesting, and incrementality measurement.
• Advanced degree in a quantitative or technical field.