Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
ML Researcher - Posttraining
San Francisco · San Francisco, California, United States
Live, first seen by us 60 days ago- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
On-site — work setting source
Location type: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Research — team source
Department: Research
From the employer’s posting
Before you apply
- Work authorization
- Sponsors visas
What you’ll work on
Full postingFinetune diffusion models at scale to improve image aesthetics and quality
Implement posttraining techniques such as SFT, preference optimization, RL, and distillation
Design eval suites and reward designs for the image-space RL stage
Train custom VLM reward models and LLMs for prompt expansion
Coordinate with data teams and partners on preference data and evaluation results
From the employer’s posting
Finetune diffusion models at scale to improve image aesthetics and quality.
Implement posttraining techniques ranging from supervised finetuning, preference optimization, reinforcement learning, on-policy distillation, and various distillation / acceleration techniques.
Design comprehensive eval suites and reward designs for the reinforcement learning stage focused on image space.
Train custom VLM as reward models as part of our reward design. Train custom LLMs for prompt expansion through finetuning and reinforcement learning.
Coordinate with data teams and partners to manage collection of preference data and model evaluation results.
Benefits in the posting
Full benefits wording- 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
- Please note the above benefits & perks are for full-time employees
From the employer’s posting.
About Krea
We're dedicated to making AI intuitive and controllable for creatives - our mission is to build tools that empower human creativity, not replace it.
In the employer’s words · Read in context · Company website ↗
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 5, 202660 days ago
- Recorded sightings
- 43
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Sep 1, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 60
Similar jobs usually come down between day 6 and day 69.
From 4,296 similar postings that came down. Coming down is not always a hire.
Krea is hiring
4 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- PyTorch
Where the posting names them
- Strong understanding of both LLM and diffusion post training pipelines and algorithms such as PPO, GRPO, DPO, OPD, and MOPD. - 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.
Your next step
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
Applying through Ashby
- No account needed. “Autofill from resume” at the top of the form fills the key fields from your file.
Already applied? Track this application
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
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, and with Krea 3 - our new image editing model.
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
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
Finetune diffusion models at scale to improve image aesthetics and quality.
Implement posttraining techniques ranging from supervised finetuning, preference optimization, reinforcement learning, on-policy distillation, and various distillation / acceleration techniques.
Design comprehensive eval suites and reward designs for the reinforcement learning stage focused on image space.
Train custom VLM as reward models as part of our reward design.
Train custom LLMs for prompt expansion through finetuning and reinforcement learning.
Coordinate with data teams and partners to manage collection of preference data and model evaluation results.
Work on safety alignment of our models for open source release.
Collaborate with our AI research and engineering teams to integrate advancements into our products.
What we're looking for
Proven work of posttraining diffusion models for image or video generation.
Experience with large-scale model training, inference, and optimization.
Strong understanding of both LLM and diffusion post training pipelines and algorithms such as PPO, GRPO, DPO, OPD, and MOPD.
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.
Good knowledge of low precision training / inference in FP8, NVFP4, and MXFP8.
Good understanding of algorithms and techniques used in fast inference engines such as vLLM and sglang as well as existing RL frameworks in LLM space such as slime, miles, tinker, and verl.
Understanding of various RL infrastructure and optimization techniques such as async RL, fast weight transfer, pipelining rollouts, managing off policy data.
Ability to monitor model regression and identify weak areas and turn them into concrete evals and reward design.
Experience training VLM models. Many of our custom reward models use VLM to provide reward signals for our models.
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.
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
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
San Francisco, California, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
- 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!