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# Machine Learning Engineer

- **Company:** Raspberry AI, Inc.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Computer-Aided Design, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Machine Learning, Open Source Technology, Google Cloud, Pytorch, Large Language Models, Deep Learning, Generative AI, Information Technology, Variational Autoencoders, Api Design
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/senior-machine-learning-engineer-raspberry-ai-8119794

## About the Role

* Master's or Ph.D. in Computer Science, Machine Learning, or a related field. 3+ 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.
 * Ability to effectively present complex technical information to both technical and non-technical audiences.

## Description

This is a full-time remote role for a Senior Machine Learning Engineer at Raspberry AI. We are seeking a highly talented and motivated Machine Learning Engineer to join our growing ML team. In this role, you will focus on improving the quality and performance of our cutting-edge diffusion models, pushing the boundaries of generative AI in the fashion domain.

Additional responsibilities may be assigned as business needs evolve., * 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.


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