Creatify provides AdMax, an AI platform that analyzes high-performing TikTok and Instagram campaigns to generate dozens of tailored social video ads for marketers to scale production and testing.
About Creatify Creatify is building the world’s first end-to-end AI advertising agent—a platform that automates the entire video ad lifecycle, from scripting and avatar-led generation to testing, optimization, and publishing across Meta, TikTok, YouTube, and more. We’ve surpassed 3 million users across 18,000+ teams. Leading brands—including Applovin, Alibaba, HubSpot, Binance, NewsBreak, and Zumper—use Creatify to produce personalized, high-performing video ads in minutes. We have raised $24M in funding from leading Silicon Valley firms including WndrCo, Kindred Ventures, Millennium New Horizons, NFDG, Comcast Ventures, Creator Ventures, Leadout Capital, Hat Trick Capital, and many more. Check out our latest coverage by Fast Company https://www.fastcompany.com/91344416/jeffrey-katzenberg-bets-big-on-ai-video-ads-with-a-15-5-million-investment-in-creatify, TechCrunch https://techcrunch.com/2025/06/02/former-dreamworks-ceo-jeffrey-katzenberg-co-leads-15-5m-series-a-for-ai-video-ad-platform/, Bloomberg TV https://www.bloomberg.com/news/videos/2025-05-28/jeffrey-katzenberg-says-ai-is-not-the-end-of-hollywood-video, and our recognition as one of IVP Enterprise AI 55 in 2024 https://www.ivp.com/content/the-ivp-enterprise-ai-55-2024/. Based in Mountain View, we are a team of passionate AI researchers, engineers, and advertising veterans. Join us in reinventing the advertising industry with AI. ABOUT THIS ROLE We’re hiring a Machine Learning Engineer to design and scale advanced models and systems for prediction, recommendation, and generative AI. In this role, you’ll work on large-scale applied ML problems, build state-of-the-art solutions, and mentor junior engineers while occasionally leading projects. This is a full-time, in-person position based in Mountain View, CA. RESPONSIBILITIES - Research, design, develop, and test operating-systems–level software, compilers, and network distribution software for massive social data and prediction problems. - Bring extensive industry experience across ranking, classification, recommendation, and optimization problems (e.g., payment fraud, CTR/CVR prediction, click-fraud detection, ads/feed/search ranking, text/sentiment classification, collaborative filtering/recommendation, spam detection), or expertise in modern generative and foundation model approaches (e.g., LLMs, transformers, diffusion models). - Tackle large-scope problems; develop highly scalable systems, algorithms, and tools leveraging deep learning, data regression, and rules-based models. - Suggest, collect, analyze, and synthesize requirements and identify bottlenecks across technology, systems, and tools. - Build solutions that iterate quickly, efficiently leverage orders of magnitude more data, and explore state-of-the-art deep learning techniques. - Demonstrate strong engineering craft and operate with minimal guidance while mentoring junior engineers. - Apply advanced ML methods to fully exploit modern parallel environments (e.g., distributed clusters, and GPU). - Lead small teams or projects where necessary, providing technical guidance, code reviews, and architectural direction. QUALIFICATIONS - Bachelor’s degree (or foreign equivalent) in Computer Science, Engineering, Applied Sciences, Mathematics, Physics, or a related field. - 4+ years of industry experience in software engineering or applied machine learning roles (E5+ or equivalent). - Proven track record of delivering large-scale systems and solving complex applied ML problems in production. - Prior experience in a tech lead (TL) capacity, such as driving technical direction, mentoring teammates, or coordinating cross-functional projects. We are an equal opportunity employer and highly value diversity at our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.