K
Kreavia Ashby
ML Researcher - Image / Video Diffusion
San FranciscoPosted 3d ago
ML EngineerMid LevelFull-time
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About the 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 https://www.krea.ai/blog/krea-2-image-model, 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 an experienced Researcher with engineering skills who can work on large-scale image and video models training experiments, with experience training image models at scale.
OUR CULTURE
- We work full-time and in-person at our North Beach office in San Francisco.
- We believe that demonstrated interest in the creative space is key: our team includes musicians, designers, visual artists and more.
- Fast iteration and execution speed. Bias towards action, agency, and independence.
WHAT YOU'LL DO
- Train diffusion models for image and video generation on large GPU clusters.
- Fully optimize and profile large distributed training runs across model architectures, kernels, data loading, memory constraints, and communication.
- Implement and improve various distributed training strategies including FSDP, CP, SP, TP, and EP.
- Continuously improve model quality and reliability through data, model architecture, training pipeline, structuring experiments, and eval design.
- Debug distributed training errors and implement fault tolerance solutions, identifying bad GPU, NVLink, Infiniband (IB) components as well as monitoring numerical errors and NCCL issues.
- Ablate different architecture, attention, optimizer, data, and algorithmic choices to reliably improve efficiency and performance of our models.
WHAT WE'RE LOOKING FOR
- Proven track record in working with image or video models at scale (publications or open-source contributions a plus).
- Strong proficiency in PyTorch and understanding of its inner workings.
- Strong background in distributed training paradigms such as FSDP, CP, SP, USP, TP, and EP. Knowing how different parallelism strategies work together and their tradeoffs.
- Experience in profiling and debugging large distributed training. Being comfortable with analyzing traces to identify bottlenecks and look for improvements.
- Good knowledge of low precision training / inference in FP8, NVFP4, and MXFP8.
- Solid understanding of diffusion model training pipeline across pretraining, midtraining, preference optimization, and reinforcement learning.
- Keeping up with the developments in related fields such as LLM, VLM, representation learning, and robotics research.
- Being comfortable working in a goal-oriented research environment.
- Having good judgement around when one should explore different training strategies and when it's time to commit to a specific strategy to scale compute and data.
- Comfortable working with underspecified goals. We expect every technical member to take an ambiguous research goal and break it down into concrete requirements, plans, experiment plan, and execution items.
- Good research taste — bias towards simplicity and methods that scale well with compute, data, and minimal human supervision.
- Ability to iterate rapidly, and propose creative research directions.
- Be comfortable getting your hands dirty with data and designing custom data pipelines to improve data quality.
WHAT WE OFFER
- Team: Work alongside a world-class team building the future of AI creative tooling
- Impact: Significant scope and company-wide impact
- Competitive compensation: generous salary & equity packages
- Health & wellness: 100% health & 99% dental/vision insurance premiums covered for employees, health FSA accounts, & long-term disability coverage
- Time off: Flexible PTO policy
- Financial planning: 401k with a 4% company-sponsored match
- Meals in the office: breakfast, lunch, dinner - you name it, we'll cover it
- Transit: Ubers covered to & from the office
- Sponsorship: We're open to sponsoring international visas where we can (e.g., STEM OPT, OPT, H-1B, O-1, E-3).
- And more!
Please note the above benefits & perks are for full-time employees
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 https://www.krea.ai/blog/krea-2-image-model, 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 an experienced Researcher with engineering skills who can work on large-scale image and video models training experiments, with experience training image models at scale.
OUR CULTURE
- We work full-time and in-person at our North Beach office in San Francisco.
- We believe that demonstrated interest in the creative space is key: our team includes musicians, designers, visual artists and more.
- Fast iteration and execution speed. Bias towards action, agency, and independence.
WHAT YOU'LL DO
- Train diffusion models for image and video generation on large GPU clusters.
- Fully optimize and profile large distributed training runs across model architectures, kernels, data loading, memory constraints, and communication.
- Implement and improve various distributed training strategies including FSDP, CP, SP, TP, and EP.
- Continuously improve model quality and reliability through data, model architecture, training pipeline, structuring experiments, and eval design.
- Debug distributed training errors and implement fault tolerance solutions, identifying bad GPU, NVLink, Infiniband (IB) components as well as monitoring numerical errors and NCCL issues.
- Ablate different architecture, attention, optimizer, data, and algorithmic choices to reliably improve efficiency and performance of our models.
WHAT WE'RE LOOKING FOR
- Proven track record in working with image or video models at scale (publications or open-source contributions a plus).
- Strong proficiency in PyTorch and understanding of its inner workings.
- Strong background in distributed training paradigms such as FSDP, CP, SP, USP, TP, and EP. Knowing how different parallelism strategies work together and their tradeoffs.
- Experience in profiling and debugging large distributed training. Being comfortable with analyzing traces to identify bottlenecks and look for improvements.
- Good knowledge of low precision training / inference in FP8, NVFP4, and MXFP8.
- Solid understanding of diffusion model training pipeline across pretraining, midtraining, preference optimization, and reinforcement learning.
- Keeping up with the developments in related fields such as LLM, VLM, representation learning, and robotics research.
- Being comfortable working in a goal-oriented research environment.
- Having good judgement around when one should explore different training strategies and when it's time to commit to a specific strategy to scale compute and data.
- Comfortable working with underspecified goals. We expect every technical member to take an ambiguous research goal and break it down into concrete requirements, plans, experiment plan, and execution items.
- Good research taste — bias towards simplicity and methods that scale well with compute, data, and minimal human supervision.
- Ability to iterate rapidly, and propose creative research directions.
- Be comfortable getting your hands dirty with data and designing custom data pipelines to improve data quality.
WHAT WE OFFER
- Team: Work alongside a world-class team building the future of AI creative tooling
- Impact: Significant scope and company-wide impact
- Competitive compensation: generous salary & equity packages
- Health & wellness: 100% health & 99% dental/vision insurance premiums covered for employees, health FSA accounts, & long-term disability coverage
- Time off: Flexible PTO policy
- Financial planning: 401k with a 4% company-sponsored match
- Meals in the office: breakfast, lunch, dinner - you name it, we'll cover it
- Transit: Ubers covered to & from the office
- Sponsorship: We're open to sponsoring international visas where we can (e.g., STEM OPT, OPT, H-1B, O-1, E-3).
- And more!
Please note the above benefits & perks are for full-time employees
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