Applied Scientist - Multimodal

ADOBE

Base: $142,700 - $270,950 annually; location depen...
Not specified
Phd or ms in computer science or related field
5+ years experience in applied ml or generative ai
Deep expertise in diffusion models and multimodal transformers
Adobe is seeking an Applied Scientist with expertise in multimodal generative AI to join their Firefly Applied Science & Machine Learning team. The role focuses on developing advanced guardrail systems for generative models, ensuring they are safe and compliant with intellectual property standards

Job Summary

  • The role focuses on building next-generation multimodal guardrail systems to ensure generative AI is safe, controllable, and respectful of intellectual property.
  • Candidates will drive research in inference-time alignment, optimizing large multimodal systems for low-latency production deployment while maintaining alignment quality.
  • Adobe offers a competitive compensation range of $142,700 to $270,950 annually depending on the work location.

Matching Summary

Match Score: 85

Adobe is seeking an Applied Scientist with expertise in multimodal generative AI to join their Firefly Applied Science & Machine Learning team. The role focuses on developing advanced guardrail systems for generative models, ensuring they are safe and compliant with intellectual property standards.

Salary

Base: $142,700 - $270,950 annually; Location dependent: CA $187,100 - $270,950, WA $168,600 - $244,200; Equity/AIP: Not specified

Skills & Requirements

Must-have

  • PhD or MS in Computer Science or related field
  • 5+ years experience in applied ML or generative AI
  • Deep expertise in diffusion models and multimodal transformers
  • Strong background in model fine-tuning and alignment strategies
  • Proficiency in Python and PyTorch frameworks
  • Experience with Vision-Language Models (VLMs)
  • Ability to use AI coding tools for rapid prototyping

Nice-to-have

  • Publications in leading conferences like NeurIPS or CVPR
  • Experience deploying generative models to large user bases
  • Background in safety evaluation frameworks and explainability
  • Knowledge of adversarial robustness techniques
  • Cross-functional collaboration with legal and ethics teams

Key Requirements

  • PhD or MS degree required
  • 5+ years of industry or academic experience
  • Expertise in large-scale generative models
  • Not specified

Work Rights

Not specified

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