Level

Higgsfield AI

Machine Learning Engineer, Ads

Higgsfield AI is hiring a Machine Learning Engineer, Ads. It pays $165k-$230k a year and Level rates it ; you can apply on Higgsfield AI.

Level's read on this job

  • On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
  • The posting allows some remote work.
  • Tools and skills the posting cites include PyTorch, TensorFlow and prompt engineering.
  • Level classifies it as a senior role.
  • Level lists 95 other open roles at Higgsfield AI.

AI in this role

Build machine learning systems and generative AI models for large-scale advertising platforms.

pytorchtensorflow
prompt-engineeringfine-tuningai-evaluationmachine-learningranking-and-recommendationml-infrastructure
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

How we rate this

Machine Learning Engineer, Ads at Higgsfield AI rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringFine-tuningAI EvaluationMachine learningRanking And RecommendationML InfrastructurePyTorchTensorFlow

Also common in machine learning engineer jobs at this level

Pay

This job starts at
$165k
Typical machine learning engineer job
$199k

This posting starts 17% below the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  3. How do you decide that one model's output is better than another's for a given task?
  4. Tell me about a project where machine learning was part of your work. What did you do?
  5. Tell me about a project where ranking and recommendation was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Prompt engineering, Fine-tuning, AI Evaluation, Machine learning, and Ranking And Recommendation. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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