Research Scientist / Engineer - Controllability, Personalization & Productization

What You’ll Do

• Work as a fullstack researcher across modeling, data, systems, and evaluation to translate foundational capabilities into personalized and high-fidelity tools for creative production.
• Controllability and Features: Use SFT, RL, distillation, and adapter-based methods to give models precise control and creative capabilities for high-fidelity workflows.
• Personalization: Use context management, PEFT, and preference learning to embed domain expertise and long-horizon memory; ground data engine in real-world workflows.
• End-User Quality: Define success metrics, build user-aligned evaluations, and iterate on model/data/evals loop for fidelity and reliability in specific verticals.
• Cross-functional Collaboration: Partner with Product and Design to turn creative intent and user feedback into specs and shippable model behaviors.

Who You Are

• Strong foundation in machine learning with deep experience in visual generative models (diffusion/transformers or related architectures).
• Deep understanding of at least one: fine-tuning, personalization, domain adaptation, data curation, targeted distillation, interpretability, or human-feedback-driven refinement.
• Product-obsessed researcher/engineer focused on end users and partners.
• Hands-on experience with PyTorch and large model training.

Bonus Points

• Contributions to state-of-the-art models in image/video generation.
• Experience collaborating with creative partners (VFX, animation, film, design tools).
• Track record building workflows/tools that improve iteration speed and evaluation rigor.
• Familiarity with large-scale training infrastructure and distributed systems (Ray, Slurm, Kubernetes).

Compensation

Base pay range: $187,500 – $395,000 per year.