Own the ML stack end-to-end: Evaluate hosted models, fine-tune open-source ones, and build scalable pipelines for image, video, and text generation.
Develop brand-aligned generation systems: Create techniques for tone, color, and style fidelity across mediums.
Improve generation quality: Build internal evaluation frameworks to measure realism, brand match, and creative diversity.
Prototype and ship: Rapidly turn research ideas into productized APIs that power Arcade’s content generation features.
Collaborate cross-functionally: Work with design and marketing to define what “on-brand” means, and with engineers to integrate ML systems into production.
Lay the foundation for content optimization: Build data pipelines connecting engagement metrics to model tuning.

Requirements

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.

Benefits

Unlimited PTO
Rich health/401(k) plans
Meeting-light culture
Remote stipend
Biannual retreats

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonML engineeringfine-tuning modelstraining modelsimage generationvideo generationtext generationevaluation frameworksgenerative modelsdata pipelines

Soft Skills

collaborationcross-functional teamworkcreativityproblem-solvingcommunication