Member of Technical Staff - Image / Video Generation

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

EUR 130K-340K not verified - source not recorded; timestamp not recorded

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

U.S. benchmark only; posted salary is not compared across countries or currencies.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Member of Technical Staff - Image / Video Generation Freiburg (Germany) About Black Forest Labs We're the team behind Latent Diffusion, Stable Diffusion, and FLUX-foundational technologies that changed how the world creates images and video. We're creating the generative models that power how people make images and video-tools used by millions of creators, developers, and businesses worldwide. Our FLUX models are among the most advanced in the world, and we're just getting started. Headquartered in Freiburg, Germany with a growing presence in San Francisco, we're scaling fast while staying true to what makes us different: research excellence, open science, and building technology that expands human creativity. Why This Role You'll train large-scale diffusion models for image and video generation, exploring new approaches while maintaining the rigor that helps us distinguish meaningful progress from incremental tweaks. This isn't about following established recipes-it's about running the experiments that clarify which architectural choices matter and which are less impactful. What You'll Work On - Trains large-scale diffusion transformer models for image and video data, working at the scale where intuitions break and empirical evidence matters - Rigorously ablates design choices-running experiments that isolate variables, control for confounds, and produce insights you can actually trust-then communicating those results to shape our research direction - Reasons about the speed-quality tradeoffs of neural network architectures in production settings where both constraints matter simultaneously - Fine-tunes diffusion models for specialized applications like image and video upscalers, inpainting/outpainting models, and other tasks where general-purpose models aren't enough What

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