Senior Machine Learning Engineer

We’re looking for a product-minded machine learning engineer who’s excited to push the boundaries of what’s possible with AI. At Arcade, you’ll experiment with the latest models to generate visuals, motion, and language that capture brand personality — crafting the foundation for content that builds and improves itself.

This is a highly collaborative and high-impact role. You’ll partner closely with design, engineering, and product to build and customize machine learning models. Expect to move fast, own ambitious projects, and see your ideas shape the way people tell product stories.

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Strong Python + ML engineering background (PyTorch, diffusers, transformers, or similar).

• Minimum 5 years experience with hands-on experience fine-tuning or training open-source models.

• Deep familiarity with modern inference and training tooling (LoRA, PEFT, DeepSpeed, Ray, Hugging Face, etc.).

• Portfolio or prior work demonstrating creative use of generative models (visuals, videos, text, etc.).

• Comfort operating across research, engineering, and product — shipping real features, not just experiments.

• (Nice to have) Familiarity with TypeScript/Next.js and integrating ML APIs into frontend products.

• Located in or willing to relocate to the Bay Area; occasional in-person collaboration required.

• Be part of a small, highly technical team where engineers ship bold ideas end-to-end.

• Work in a culture that values openness, ownership, collaboration, and kindness.
  Enjoy perks like unlimited PTO, rich health/401(k) plans, meeting-light culture, remote stipend, and biannual retreats.

• Enjoy working on site in San Francisco on Tuesdays and Thursdays.

• Be a coach: We want the best for our customers and ourselves. We coach people to help them achieve their best potential. An “Arcader” is both a teammate and a customer. There is a reason that the same word describes both.

• Carry the weight: We are owners. Let’s empower each other. When we see something that needs change, we lead through it.

• An open book: We are open as a team and as a product. We don’t put walls up unless it’s necessary. We become better when we share information. We are open to diversity of opinion, backgrounds, and thought.

• Play as a team: We play because we’re a creator tool. Life is short. Let’s build something meaningful. We play as a team because great teams build great things together. We keep those standards high.

• Be kind: We can be honest and kind. We can have high standards and be kind. We can say no and be kind. Kindness can vary across cultures, upbringings, and languages - but we try our best to be kind.