Machine Learning Engineer, Ads
At a glance
Mid-level Machine Learning Engineering role at Higgsfield. San Francisco · full-time · $165,000–$230,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Create and refine ad ML for ranking, recommendations, audience targeting, prediction and optimization
- Feed advertising performance signals back into generative systems to improve the creative they produce
- Use prompting, model adaptation and evaluation to tailor foundation models to advertising goals
- Run tests across creative generation, ranking, targeting and delivery to identify what lifts advertiser results
- Move production ML from experiments into dependable inference and serving at significant scale
What you bring
- You have substantial hands-on work building machine learning systems for advertising
- You understand ad mechanisms such as ranking, recommendations or bidding, and have used generative AI models
- You have applied prompt engineering, model evaluation and post-training methods such as fine-tuning or preference optimization
- You have shipped production ML software and can turn experiments into scalable systems
- You can work in English
Who this fits
This mid-level role suits an engineer who can span advertising ML, generative models and production engineering. It is hybrid in the San Francisco Bay Area, with three full office days each week. You should be available during agreed working hours and overlap with your team’s time zone.
From the employer
Why work at Higgsfield AI?
Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands.
We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like.
About the role
We're looking for exceptional Machine Learning Engineers focused on Ads to help take Higgsfield's advertising platform to the next level.
You'll work at the intersection of large-scale machine learning, generative AI, and advertising systems—building the models and infrastructure that determine how creative is generated, ranked, optimized, and ultimately performs.
This role is for someone who understands ads systems deeply and is equally strong in modern generative AI. You should be comfortable moving across ranking and recommendation, targeting and optimization, prompt engineering, post-training, and production ML systems.
You'll help define what an AI-native advertising platform looks like from the ground up.
What you'll do:
Build and improve ML systems powering advertising products, including ranking, recommendation, targeting, prediction, and optimization.
Develop models that improve ad creative quality, relevance, personalization, and performance at scale.
Build systems that connect generative models with real-world advertising performance signals, creating feedback loops that continuously improve model outputs.
Apply prompt engineering and post-training techniques to improve generative models for advertising and creative use cases.
Work on fine-tuning, preference optimization, evaluation, and other techniques for adapting foundation models to specific creative and advertising objectives.
Design and run experiments across creative generation, ranking, targeting, and delivery to understand what drives advertiser performance.
Build production ML systems that operate reliably at significant scale, from experimentation through inference and serving.
Work closely with Product, Research, Engineering, and GTM teams to turn advances in generative AI into products advertisers can use.
Requirements
Deep experience building machine learning systems for advertising.
Strong understanding of ads systems, including areas such as 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 and model evaluation.
Experience with post-training, including techniques such as supervised fine-tuning, preference optimization, reinforcement learning, or related approaches.
Strong software engineering fundamentals and experience shipping production ML systems.
Ability to operate across research and engineering: you can experiment quickly, identify what works, and turn it into a scalable production system.
High agency.
Working English.
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 using downstream signals such as CTR, CVR, ROAS, engagement, or retention to train or optimize ML systems.
Experience with large-scale model training, inference optimization, or distributed ML infrastructure.
Experience building AI systems that generate or optimize advertising creative.
Compensation & Benefits
• We offer a competitive and thoughtfully structured compensation package designed to align with impact, experience, and long-term growth.
• Base Salary: The anticipated salary range for this role is $165 - $230k, depending on experience, skills, scope, and location.
• Equity: In addition to cash compensation, employees are eligible to participate in the company’s stock option program and share in Higgsfield’s long-term growth. •
• Benefits: We offer a comprehensive benefits package designed to support employees professionally and personally
• The opportunity to work on ambitious AI products alongside a highly experienced, fast-moving, and international team.
• Significant ownership, direct impact, and opportunities for professional growth as the company scales.
This is a hybrid role based in the San Francisco Bay Area. Team members are expected to work from our San Francisco office three full days per week, with the remaining days worked remotely and are expected to be available during agreed working hours and to maintain sufficient overlap with the relevant team’s time zone. We value in-person collaboration, active communication, responsiveness, and close partnership across teams.
Higgsfield AI is an equal opportunity employer. We are committed to building a diverse and inclusive team and do not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual