Evaluate new image generation and identity preservation papers and models.
Develop and deploy new versions of the image generation and image analysis pipelines
Monitor and fix production issues that impact users
Fine-tune and optimize models to improve character consistency, prompt responsiveness, and inference latency
Design and run experiments to benchmark model performance, tracking quality metrics across generations of pipeline improvements
Collaborate with cross-functional teams to translate product requirements into ML solutions and bring new generative features from prototype to production

Demonstrated interest in AI image generation. This includes both personal and professional projects
Deep technical foundation in machine learning specifically in image synthesis
5+ years experience as a software engineer, preferably in services
2+ years of experience of building production-grade machine learning models in industry and/or academic research settings
Strong programming skills in Python and deploying Python based services
Familiarity with tools and frameworks involved in AI image generation including but not limited to Stable Diffusion, Diffusion Transformers (DiT), Visual Transformers (ViT), Tensorflow, PyTorch, Diffusers, ComfyUI, TensorRT, and CUDA
Experience building end-to-end scalable ML infrastructure with on-premise or cloud platforms including Baseten, Google Cloud Platform (GCP), Amazon Web Services (AWS) or Azure
Strong teamwork skills including communication and collaboration with both technical and non-technical team members

Machine Learning Engineer, Images

Key skills