Black Forest Labs
generative AI
ForwardDeployedMachineLearningEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Forward Deployed Machine Learning Engineer at Black Forest Labs. Skills: Forward Deployed Machine Learning Engineering, Generative AI Deployment, Diffusion Models, Production ML Systems, Customer-facing ML Solutions. Ensure FLUX models perform optimally in customer environments. balance the eternal tension between latency and output quality”
What You'll Achieve.
Ensures FLUX models perform optimally in customer environments; bring frontier generative AI into production at scale
Industry & Context.
debugged them, optimized them, served them at scale; diagnose whether it's a model issue, an infrastructure issue, or a fundamental misunderstanding of what the model can do; diagnose performance bottlenecks; translate those findings into solutions
work remotely with a monthly in-person week to stay connected, cover reasonable travel costs to make this possible
What They're Looking For.
Must Have
Direct experience working with customers on generative AI deployment, Hands-on expertise with generative modeling approaches, particularly finetuning, optimizing, and serving deep learning models in production environments, A proven track record as an ML engineer who's shipped models that real systems depend on, Python skills and intuitive understanding of API design, The ability to explain why a diffusion model is slow to an executive and how to fix it to an engineer
Nice to Have
Deep knowledge of diffusion models and/or flow matching, including finetuning and distillation techniques that go beyond standard tutorials, Know the FLUX ecosystem intimately—ComfyUI, common training frameworks, the tools practitioners actually use, Battle-tested experience optimizing inference for transformer-based models, Can architect solutions in complex enterprise environments where "just add more GPUs" isn't an option, Contribute to open-source projects in the diffusion model space and understand the community, Deployed models on cloud platforms using state-of-the-art serving infrastructure
What You'll Do.
Ensure FLUX models perform optimally in customer environments
balance the eternal tension between latency and output quality
Architect deep product integrations
help customers with everything from model hosting and deployment to inference optimization techniques
Customize foundation models for visual media
Sits in technical deep-dives with customers
diagnose performance bottlenecks
translate those findings into solutions
Discovers where generative visual AI should go next by understanding what industries are struggling with problems we could solve
How You'll Work.
Team & Collaboration
Sits in technical deep-dives with customers; translate those findings into solutions (and sometimes into research questions for our core team); figuring these out together; collaboration over hero culture
Communication Scope
explain why a diffusion model is slow to an executive and how to fix it to an engineer—in the same meeting; honest technical conversations
Full Job Description
What if the hardest part of generative AI isn't training the model, but making it work in production under constraints no one anticipated? Our founding team pioneered Latent Diffusion and Stable Diffusion - breakthroughs that made generative AI accessible to millions. Today, our FLUX models power creative tools, design workflows, and products across industries worldwide. Our FLUX models are best-in-class not only for their capability, but for ease of use in developing production applications. We top public benchmarks and compete at the frontier - and in most instances we're winning. If you're relentlessly curious and driven by high agency, we want to talk. With a team of ~50, we move fast and punch above our weight. From our labs in Freiburg - a university town in the Black Forest - and San Francisco, we're building what comes next. What You'll Pioneer You'll live at the intersection of cutting-edge research and brutal production reality. Your customers won't just want FLUX to work—they'll need it optimized for their specific hardware, fine-tuned for their unique use cases, and integrated into systems that weren't designed for diffusion models in the first place. You'll be the person who: Ensures FLUX models perform optimally in customer environments—whether that's on-premise GPU clusters or BFL-hosted infrastructure—balancing the eternal tension between latency and output quality Architects deep product integrations that go far beyond "here's an API endpoint"—helping customers with everything from model hosting and deployment to inference optimization techniques that haven't made it into textbooks yet Customizes our foundation models for visual media to solve problems customers couldn't articulate until you helped them understand what's possible Sits in technical deep-dives with customers to diagnose performance bottlenecks, then translates those findings into solutions (and sometimes into research questions for our core team) Discovers where generative visual AI s
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