ML Researcher
Posted 1 Sep 2026
Advertised as “ML Researcher - Posttraining”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Full-time
- Visa sponsorship
- Offered
No salary listed for this role.
About Krea
At Krea, we are building next-generation AI creative tools.
We're dedicated to making AI intuitive and controllable for creatives - our mission is to build tools that empower human creativity, not replace it. We believe AI is a new medium that allows us to express ourselves through various formats - text, images, video, sound, and even 3D. We're building better, smarter, and more controllable tools to harness this medium. We recently took this a step forward with the launch of Krea 2, our first foundation model, built completely from scratch for aesthetic diversity and stylistic control.
We've raised over $83M and are backed by world-class investors such as a16z, Bain Capital, and Abstract. We work full-time and in-person at our waterfront office in San Francisco. We care about creativity: our team includes musicians, designers, visual artists, and engineers.
We're looking for someone with deep experience in large-scale finetuning of diffusion models and posttraining techniques. We have loads of high-quality data and aim to enhance the quality and aesthetics of the models we're building.
Our culture
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We work full-time and in-person at our North Beach office in San Francisco.
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We believe that demonstrated interest in the creative space is key: our team includes musicians, designers, visual artists and more.
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Fast iteration and execution speed. Bias towards action, agency, and independence.
What you'll do
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Finetune diffusion models at scale to improve image aesthetics and quality.
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Implement posttraining techniques ranging from supervised finetuning, preference optimization, reinforcement learning, on-policy distillation, and various distillation / acceleration techniques.
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Design comprehensive eval suites and reward designs for the reinforcement learning stage focused on image space.
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Train custom VLM as reward models as part of our reward design.
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Train custom LLMs for prompt expansion through finetuning and reinforcement learning.
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Coordinate with data teams and partners to manage collection of preference data and model evaluation results.
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Work on safety alignment of our models for open source release.
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Collaborate with our AI research and engineering teams to integrate advancements into our products.