Senior Machine Learning Engineer

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🕒 October 22, 2025

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Raspberry AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

📣 Marketing

🤖 Artificial Intelligence

Consulting • Marketing • Artificial Intelligence

Raspberry AI is a generative AI platform and creative assistant for fashion brands and designers that automates design and visual content creation. It generates prints, patterns, product graphics, and photorealistic renderings (sketch-to-render, photography and video studio outputs), and offers brand-customized AI models, private hosting, and enterprise workflows to speed concept-to-market, reduce sampling costs, and retain IP. The product is positioned as a B2B SaaS tool used by retailers, apparel manufacturers, and design teams to iterate faster and scale visual merchandising and product development.

📋 Description

• 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.

🎯 Requirements

• 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.