We are looking for research engineer with extremely strong technical experience in training Generative AI models. You’ll be part of the research team, helping build our core multimodal foundation models and manage training runs across thousands of GPUs.
Responsibilities
Lead and contribute to cutting-edge research in multimodal foundation models
Design, develop, and experiment with novel algorithms, architectures, and techniques that enhance the performance, efficiency, and scalability of our AI models.
Optimize the performance of models for deployment in production environments, focusing on latency, throughput, and computational efficiency without compromising accuracy or robustness.
Inspect and manage large-scale data clusters to find inefficiencies and bottlenecks in model training, and data loading
Collaborate with cross-functional teams including data, applied research and infrastructure
Experience
Very strong demonstrated engineering ability in Python and Pytorch.
Experience building ML models from scratch in Pytorch.
Academic or Professional experience with (and understanding of) generative multimodal models such as Diffusion Models and GANs, as well as deep learning concepts such as Transformers.
Good to have familiarity with Linux clusters, systems & scripting.
Good to have experience working with large distributed systems (>100 GPUs).
Compensation
The pay range for this position in California is $180,000 - $250,000yr; however, base pay offered may vary depending on job-related knowledge, skills, candidate location, and experience. We also offer competitive equity packages in the form of stock options and a comprehensive benefits plan.
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