Job description
Research Scientist - Generative AI Models
$200,000 - $300,000 + Market Leading Equity + Benefits + PTO
Palo Alto, CA - On-site
Are you a visionary researcher passionate about unlocking the potential of multimodal AI? Do you want to work at the forefront of generative AI research, tackling complex challenges with real-world impact?
This is an extraordinary opportunity to join an AI startup that's pushing the limits of what's possible in generative AI. Backed by top-tier investors ($xxx million in funding) and a world-class technical team, they're pioneering breakthroughs in large language models, diffusion models, and multimodal generative technologies.
I'm working with a well-funded Palo Alto-based AI company that's expanding its research team. They are seeking Research Scientists to help develop and optimize generative AI models across video, image, text, audio, and 3D. In this role, you'll work on state-of-the-art models and systems that unlock the next generation of AI capabilities.
This is a rare opportunity to join a world-class applied research team, work with massive GPU clusters, and help shape the future of multimodal AI, whilst benefiting from an excellent equity and compensation, and supercharging your career progression.
The Role
* Develop and train generative AI models across multiple modalities (video, image, text, audio, 3D).
* Contribute to optimizing models for real-world applications such as controlled generation, editing, and reinforcement learning.
* Innovate on large-scale distributed systems for training and inference efficiency.
* Curate and process high-quality datasets for pretraining and fine-tuning generative models.
* Collaborate closely with research scientists, engineers, and cross-functional teams to deploy cutting-edge models.
* On-site in Palo Alto, CA
Ideal Candidate
* Strong background in deep learning frameworks like PyTorch and/or JAX.
* Hands-on experience developing and training multimodal generative models.
* Familiarity with reinforcement learning, model optimization, and distributed systems.
* Experience in data curation, processing, and model fine-tuning.
* Passion for advancing generative AI research and real-world applications.
