AI Applied Scientist

About Arcade

Arcade is building the world’s first AI physical product creation platform, where imagination becomes reality. Our platform lets anyone design, purchase, and sell custom, manufacturable products using natural language and generative AI. We believe everyone should have the power to create physical goods as easily as they post online, and we’re building the infrastructure to make that real.

We’ve raised $42M from a world-class group of investors, including Reid Hoffman, Forerunner Ventures (Kirsten Green), Canaan Partners (Laura Chau), Adverb Ventures (April Underwood), Factorial Funds (Sol Bier), Offline Ventures (Brit Morin), Sound Ventures (Ashton Kutcher), Inspired Capital (Alexa von Tobel), and Torch Capital (Jonathan Keidan). Our angel investors include Elad Gil, Ev Williams, Marissa Mayer, Sara Beykpour, Kayvon Beykpour, Anna Veronika Dorogush, Eugenia Kuyda, David Luan, Sharon Zhou, Kelly Wearstler, Karlie Kloss, Colin Kaepernick, Christy Turlington Burns, and Jeff Wilke.

Arcade is headquartered in San Francisco’s Presidio and led by serial entrepreneur Mariam Naficy (Minted, Eve), and a founding team with deep experience in generative AI, design systems, and supply chain. We’re pioneering a new category at the intersection of AI, personal expression, and on‑demand manufacturing, and we’re building fast.

• We are looking for a highly skilled AI Applied Scientist to advance our generative AI capabilities, with a focus on improving the outputs of diffusion and multi‑modal transformer models to meet consumer product needs across many dimensions, from resolution to faithfulness and more. This role will be instrumental in shaping how AI transforms commerce.
• As a key member of our AI team, you will conduct cutting‑edge research, prototype new AI models, and develop new modes of consumer interaction with AI. Your work will drive how users interact with and leverage AI ond technical contributions, you will keep the team at the forefront of AI advancements, ensuring we integrate the latest research into our products.
• This role blends deep technical research, product thinking, and hands‑on implementation, requiring someone who thrives in a fast‑paced, evolving environment.
• This is a hybrid role (3-4 days per week on‑site) at Arcade’s office in the Presidio, San Francisco.
• Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

• Design, build, and evaluate novel generative AI models and high‑resolution image models, including training, image generation, and editing, inclusive of both diffusion‑based and transformer‑based techniques.
• Develop and deploy multi‑modal architectures that combine vision, language, and structured data for AI‑powered product creation.
• Stay ahead of emerging AI advancements, ensuring Arcade remains at the cutting edge of generative AI and computer vision.
• Implement and maintain automated training pipelines for scalable experimentation. Build AI‑driven internal tools that improve efficiency, automation, monitoring and content generation.
• Deploy AI models into production, ensuring they are optimized for real‑world applications.
• Optimize AI models for scalability, reliability, and performance in production environments.
• Collaborate with cross‑functional teams to integrate AI into consumer‑facing products for seamless user experiences.

This role is ideal for someone who thrives at the intersection of research, engineering, and product innovation, ensuring AI advancements translate into real‑world impact at Arcade.

• Bachelor’s in Computer Science, Mathematics, Engineering, or related field (Master’s or PhD preferred).
• Builds and is in active contact with network of applied AI scientists and engineers.
• Research experience in AI/ML, with a focus on diffusion models and computer vision.
• Demonstrated experience applying generative models in production / commercial applications, including the orchestration layers and pipeline architecture needed to successfully use models to solve problems, and the deploying, monitoring, and iterating of models in…