Forward Deployed Machine Learning Engineer

Black Forest Labs is a cutting-edge startup pioneering generative image and video models. Our team, which invented Stable Diffusion, Stable Video Diffusion, and FLUX.1, is currently looking for a Forward Deployed MLE to help us take our core offerings and expertise to the hands of our critical customers.

We are looking for candidates with a strong understanding and a clear grasp of the inner workings of generative models - diffusion models especially - as well as prior hands-on experience in inference optimization. Additionally some experience serving these models via APIs would be a bonus. You should enjoy working with customers, better understand their needs and assist them with BFL models such as help with finetuning FLUX models for their specific use case.

As a Forward Deployed Machine Learning Engineer for BFL you will:

• Help customers to set up FLUX models in their services and ensure an optimal performance in terms of latency and output quality, both for on premise deployments and BFL-hosted integrations.
• Design and implement deep product integrations for customers, and help them with model hosting, finetuning, deployment and inference optimization
• Customize foundation models for visual media for customer specific use cases
• Meet with customers to identify gaps and pain points, assess their needs for BFL’s solutions, and help them to decide between BFL-hosted and on premise deployments
• Collaborate with customers to identify relevant use cases and find innovative solutions for solving these
• Identify expansion potentials for BFL’s technologies into new industry sectors across the globe

• Experience in working directly with customers, iterating on solutions and providing tailored support for serving generative AI models
• Prior experience with common generative modeling approaches and hands-on experience with finetuning, optimizing and serving deep learning models.
• Proven track record in machine learning engineering
• Proficiency in Python and understanding of API integrations to implement basic functionality and help customers with prototyping/demo building.
• Experience in explaining and summarizing sophisticated technical concepts to both technical and non-technical audiences
• Excellent communication skills and experience in collaborating with non-technical stakeholders internally and externally, and the ability to adapt messaging to different audiences and explain complex technical concepts in simple terms with technical and non-technical audiences

• Prior knowledge about diffusion models and/or flow matching, and relevant finetuning and distillation techniques
• Experience in using common open source tooling around from the FLUX ecosystem such as ComfyUI and common trainer frameworks
• Experience with inference optimizations for transformer based machine learning models
• Proven ability to architect solutions in complex enterprise environments
• Contributed to open-source projects in particular in the space of diffusion models
• Experience with cloud platforms and state of the art deployment solutions for diffusion models