Why work at Higgsfield AI?

Higgsfield AI is the fastest-growing GenAI platform in the world — #1 in Video AI in the U.S. and top globally by growth.

In 9 months, we built a platform for 15M+ users, shipped 100+ releases, and scaled to 4.5M video generations per day, moving at a pace few companies in the world can match.

We’ve already earned the attention of cultural icons like Elon Musk, Madonna, Snoop Dogg, and Will Smith, and generated over 3B social impressions.

We raised a $130M Series A — and we’re only getting started. This is your chance to join early, when the team is small but mighty, and help build the next GenAI decacorn.

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Sounds interesting? Apply here.

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About the role

We are building Cursor for Video Generation — an AI-native product that reimagines how videos are created, edited, and produced using natural language and intelligent models.

We’re looking for an ML/AI Engineer who is not only technically excellent, but also creative, collaborative, and deeply curious about how video production actually works. This role sits at the intersection of machine learning, creative workflows, and video production.

You will work closely with video editors, content creators, prompt engineers, and product teams to translate creative intent and post-production workflows into scalable, intelligent systems.

What you will work on

Product & Model Development

• Design, train, and iterate on ML models for video generation, editing, and transformation, including:
  • Video synthesis and generation
  • Scene detection, cuts, transitions
  • Style, pacing, and narrative coherence
  • Text-to-video and prompt-based editing workflows
• Own the end-to-end ML lifecycle: research → prototyping → training → evaluation → deployment.
• Collaborate with product and engineering to turn models into fast, reliable, user-facing features.

Creative & Cross-Functional Collaboration

• Work hands-on with creative teams (video editors, motion designers, producers) to:
  • Understand real-world video production and post-production workflows
  • Learn how editors think about timing, rhythm, storytelling, and visual language
• Translate creative feedback and artistic intent into technical requirements, model improvements, and system design.
• Act as a bridge between creativity and engineering, ensuring the AI enhances — not replaces — creative control.