KR

ML Researcher - Image / Video Diffusion

Krea H-1BOPT Information Technology Full-timeSan Francisco, California
Posted Sep 1, 2026 · Expires Oct 16, 2026

Quick facts

Type
Full-time
Location
San Francisco, California
Skills
PyTorch
Industry
Information Technology — 671 open jobs
Visa in listing
H-1B, OPT
Apply
Free to apply — never pay anyone for a job offer or visa sponsorship

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.

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

Visa sponsorship record

No public sponsorship records found

We didn't find H-1B, H-1B1, E-3 or green card (PERM) filings under the name Krea in the Department of Labor and USCIS data. That doesn't mean the job can't be sponsored — the company may file under a different legal name, be new to sponsorship, or sponsor a visa that isn't in these datasets (for example H-2B or J-1).

Tip: ask the recruiter early, in writing, which visa they sponsor and whether they cover the legal and filing fees.

Which visas can work for this job

Occupation: Data Scientists (SOC 15-2051) — estimated from the job title.

  • Mentioned in the listing

    H-1B, OPT

  • H-1B cap-exempt employer

    Regular cap-subject employer — a new H-1B needs to win the lottery in March (unless you already hold cap-counted H-1B status).

  • TN (citizens of Canada and Mexico)

    This kind of role may fit the USMCA profession “Mathematician / Statistician” — it depends on the actual duties. No lottery, no cap; you need the matching degree or license.

  • E-3 (Australia) and H-1B1 (Chile, Singapore)

    Same degree requirement as H-1B, but no lottery and a separate quota that is rarely filled.

  • O-1 (extraordinary ability)

    For candidates with awards, publications, press, a high salary or critical roles at distinguished organizations. No cap, no lottery; the employer files a petition.

  • STEM OPT extension (F-1 students)

    Requires an E-Verify employer. We didn't find this company in the E-Verify list — ask HR.

Salary vs prevailing wage

Level II (qualified)

Data Scientists · San Francisco-Oakland-Fremont, CA. Annual prevailing wages set by the Department of Labor (OFLC).

L1L2L3L4
LevelPrevailing wageH-1B lottery odds*
Level I$110,386~15%
Level II$142,438~31%
Level III$174,512~46%
Level IV$206,565~61%

This job pays $172,640 a year (converted from an hourly rate, 2,080 hours) — that's Level II (qualified). In the wage-weighted H-1B lottery a Level II registration gets 2 entries; estimated selection chance about 31%.

* Odds are DHS projections for the FY2027 wage-weighted lottery (actual results vary by year and employer). Since the FY2027 cap season the H-1B lottery is weighted by wage level: Level I = 1 entry, II = 2, III = 3, IV = 4. The level is set by the offered wage against the prevailing wage for the occupation and worksite. Separately, a $100,000 fee for new H-1B petitions for workers outside the US was announced in 2025; as of September 2026 a federal court ruling keeps it unenforceable while appeals continue — check the current status.

Sources: U.S. Department of Labor OFLC disclosure data (H-1B/H-1B1/E-3 LCA, PERM), OFLC prevailing wage data, USCIS H-1B Employer Data Hub, E-Verify participating employers. Data loaded: LCA FY2024–FY2026, PERM, USCIS Data Hub, OFLC wages; updated 2026-10-03. Employers are matched by name, so records of companies with similar names can occasionally be mixed up. This is general information, not legal advice — talk to an immigration attorney about your case.