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 seeking a strong researcher / engineer to work closely with our research team on benchmarking and inference optimisation.

The Role:

• Benchmark our generative models against the current state-of-the-art (SOTA) across a range of tasks and datasets
  
  
• Identify strengths, weaknesses, and blind spots in model behavior and performance
  
  
• Explore and implement techniques to optimize inference performance, including speed, accuracy, and resource efficiency
  
  
• Stay up-to-date with the latest research in generative AI and contribute to internal knowledge-sharing
  
  
• Collaborate with the engineering and product teams to bring research insights into practical deployment
  
  
• Contribute to open-source efforts or publish findings, depending on interest
  
  

Required Qualifications:

• MS or PhD in Machine Learning, Computer Vision, Artificial Intelligence, or a related field
  
  
• Hands-on experience evaluating generative models (experience with diffusion models is a strong plus)
  
  
• Solid understanding of deep learning fundamentals and model evaluation techniques
  
  
• Strong programming skills in Python; familiarity with ML frameworks such as PyTorch or TensorFlow
  
  

Preferred Qualifications:

• Previous internship or research experience in generative AI or computer vision
  
  
• Demonstrated interest in the field (e.g., GitHub projects, open-source contributions, personal research)
  
  
• Familiarity with current SOTA benchmarks and relevant datasets in generative modeling