Machine Learning Engineer (Advertising AI)

Location: Hybrid role based in the San Francisco Bay Area, USA; three full days per week in the San Francisco office

Salary: $165,000–$230,000 per year, plus equity and bonus

Company

hirify.global is a generative AI company building AI-powered video creation and next-generation creative tools for millions of users and major brands.

What you will do

• Build and improve machine learning systems for advertising, including ranking, recommendation, targeting, prediction, bidding, and optimization.
• Develop models that improve ad creative quality, relevance, personalization, and performance at scale.
• Connect generative models with advertising performance signals to create feedback loops that improve model outputs.
• Apply prompt engineering, fine-tuning, preference optimization, evaluation, and post-training techniques to foundation models.
• Design and run experiments across creative generation, ranking, targeting, and delivery.
• Ship reliable production ML systems from experimentation through inference and serving while partnering with Product, Research, Engineering, and GTM teams.

Requirements

• Deep experience building machine learning systems for advertising.
• Strong understanding of ads systems, including ranking, recommendation, targeting, bidding, conversion prediction, creative optimization, or measurement.
• Hands-on experience with LLMs, multimodal models, or generative AI systems.
• Strong experience with prompt engineering, model evaluation, and post-training techniques such as supervised fine-tuning, preference optimization, or reinforcement learning.
• Strong software engineering fundamentals and experience shipping production ML systems.
• Working English and availability for three full office days per week in San Francisco, with sufficient time-zone overlap.

Nice to have

• Experience building ads, ranking, or recommendation systems at a major consumer, social, search, or advertising platform.
• Experience with generative video, image, or multimodal models.
• Experience optimizing systems using CTR, CVR, ROAS, engagement, or retention signals.
• Experience with large-scale model training, inference optimization, or distributed ML infrastructure.
• Experience building AI systems that generate or optimize advertising creative.

Culture & Benefits

• Work on ambitious AI products with an experienced, fast-moving, and international team.
• Significant ownership, direct impact, and opportunities for professional growth.
• Stock option participation and a comprehensive benefits package.
• Hybrid work with remote days and an emphasis on in-person collaboration and active communication.