Image Generation Machine Learning Expert

Responsibilities - Design, build, and evaluate state-of-the-art image generation models including diffusion models, GANs, VAEs, and autoregressive approaches - Fine-tune and adapt pre-trained generative models for specific domains, styles, and downstream applications - Conduct rigorous evaluation of image generation quality using perceptual, statistical, and task-specific metrics - Experiment with conditioning mechanisms, guidance techniques, and controllable generation approaches - Document methodologies, experimental results, and technical approaches clearly and reproducibly

Required qualifications - Published researcher with at least one first-author publication in a peer-reviewed venue (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, or equivalent) - Master's or PhD in Machine Learning, Computer Vision, Computer Science, or a related quantitative field - Demonstrated expertise in image generation, generative modeling, or closely related areas of deep learning - Demonstrated expertise in image generation, generative modeling, or closely related areas of deep learning

Preferred qualifications - Hands-on experience with leading generative modeling frameworks and architectures (e.g., Stable Diffusion, DALL-E, Imagen, DiT, or similar) - Familiarity with fine-tuning techniques such as LoRA, DreamBooth, ControlNet, or similar methods - Experience with large-scale image datasets and distributed training pipelines - Background in TA'ing or teaching computer vision, deep learning, or generative modeling courses

Why apply - Flexible Time Commitment – Work on your schedule while tackling meaningful research challenges - Startup Exposure – Work directly with an early-stage Y Combinator-backed company, gaining hands-on experience that sets you apart - Exceptional Pay – Project-based pay ranges from $150–$200/hour - Portfolio Building – Gain experience on frontier image generation and generative modeling problems - Professional Growth – Sharpen your skills on varied, challenging visual generation tasks and datasets

Employment type: Contract Time commitment: 10 hours/week Location: Remote