Principal Machine Learning Engineer

Master's or Ph.D. in Computer Science, Machine Learning, or a related field. 5+ years of industry experience. Strong theoretical and practical understanding of deep learning, with a focus on generative models (e.g., GANs, VAEs, Diffusion Models). Hands-on experience with deep learning frameworks such as PyTorch. Experience with training and evaluating generative models on cloud GPU platforms (e.g., AWS, GCP, Azure). Proficiency in using and tuning multimodal LLMs, including experience with both API-based and open-source model implementations.

Conduct applied research and experimentation on state-of-the-art diffusion model architectures and training techniques. Implement and evaluate novel techniques for improving quality and controllability in generated designs. Analyze and interpret experimental results, draw meaningful conclusions, and communicate findings effectively. Collaborate closely with the team to translate prototypes into production-ready systems. Stay abreast of the latest advancements in diffusion models, deep learning, and generative AI research.