AI Engineering Lead

November 20

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Raspberry AI

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Artificial Intelligence • Fashion • SaaS

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.

11 - 50 employees

🤖 Artificial Intelligence

👗 Fashion

☁️ SaaS

📋 Description

• Develop and own the technical roadmap for Raspberry’s creative AI tools, spanning image generation, editing, and end-to-end design workflows. • Mentor and guide a small team of ML engineers and researchers, raising the bar on experimentation, code quality, system design, and impact. • Design and evolve the systems and model orchestration in order to improve quality, controllability, and realism in generated designs. • Conduct applied research and rapid experimentation on diffusion and other generative models, adaptation techniques, and routing strategies, and bring the most effective approaches into production. • Prototype and refine end‑to‑end design workflows for designers inside Raspberry and translate them into robust, production features. • Collaborate closely with product, design, and product engineering to shape creative workflows, quality standards, and the roadmap for AI-powered features. • Evaluate and integrate new techniques, frameworks, and open-source contributions to stay on the frontier of generative AI research. • Design and maintain pragmatic evaluation loops that combine automated metrics, LLM-assisted review, human feedback, and high-quality golden datasets. • Serve as a thought leader on AI innovation within Raspberry and across the broader industry.

🎯 Requirements

• Master’s or Ph.D. in Computer Science, Machine Learning, or a related field, or equivalent industry experience in applied ML roles. • 7+ years of experience in applied machine learning or adjacent research‑to‑product roles with tangible shipped impact, including 3+ years leading significant technical projects and/or acting as a tech lead for other engineers. • Applied technical depth in several of the following areas: computer vision for generation/editing, diffusion or other generative model adaptation, model routing/orchestration, multimodal prompting, and tool use. • Strong practical experience with generative image and/or video models, including using and adapting modern diffusion or multimodal models in production systems. • Experience training and evaluating models on cloud GPU platforms (AWS, GCP, or Azure) and integrating external model APIs alongside open‑source stacks. • Proven ability to take AI research to production, with experience building systems that balance innovation, performance, and maintainability. • Proficiency using and tuning multimodal LLMs to support prompting, routing, and evaluation workflows. • Familiarity with LLMs, CLIP-like architectures, and multimodal embeddings. Familiarity with CLIP-like architectures and multimodal embeddings, and how they integrate into generative and evaluation pipelines. • Excellent communication and collaboration skills — able to work fluidly with designers, engineers, and business leaders alike. • Passion for creative AI and its ability to transform human expression and design workflows.

🏖️ Benefits

• Competitive compensation, equity, and benefits in a remote-first environment.