Machine Learning Engineer

Location

Mountain View

Employment Type

Full time

Location Type

On-site

Department

Research

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.

In just 18 months, we’ve surpassed $10 million in ARR, serving over 1.5 million users across 10,000+ teams. Leading brands—including Alibaba, HubSpot, Binance, NewsBreak, and Zumper—use Creatify to produce personalized, high-performing video ads in minutes.

We have raised $23M in funding from leading Silicon Valley firms including WndrCo, Kindred Ventures, Millennium New Horizons, NFDG, Creator Ventures, Leadout Capital, Hat Trick Capital, and many more. Check out our latest coverage by Fast Company, TechCrunch, Bloomberg TV, and our recognition as one of IVP Enterprise AI 55 in 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

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.

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