AI Engineering Lead
Raspberry AI - United States
Posted Nov 19, 2025
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
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About this role
AI Engineering Lead United States AI Engineering Lead Raspberry AI Raspberry AI is a leading provider of industry-defining AI design software for fashion brands and retailers. Our platform empowers global brands to understand consumer demand, generate unique designs within minutes, and revolutionize how products are conceived and brought to market. Backed by Andreessen Horowitz, Khosla Ventures, MVP, and Greycroft , Raspberry AI is transforming a $2.5T industry through cutting-edge generative and multimodal AI . About the Role We are seeking an experienced AI Engineering Lead to drive the next generation of generative AI capabilities powering Raspberry's creative intelligence platform. This person will own development of Raspberry's suite of creative AI tools, spanning image generation, editing and end-to-end design workflows. They will define how models, orchestration and evaluation come together to deliver reliable and powerful design experiences for our customers, and will own the technical direction and quality of the AI systems that power the product. You'll operate at the intersection of research, engineering, and product , shaping how AI drives creativity, collaboration, and impact across the fashion ecosystem. Key Responsibilities - 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
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