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What You'll Be Doing:
Keeping abreast of the latest advancements in generative AI research.
Implementing and benchmarking cutting-edge large language and multi-modal models, analyzing their emergent patterns and system performance bottlenecks.
Pioneering the development of innovative optimizations to effectively lower the operational costs associated with deploying generative AI models at large scale.
Collaborating closely with production teams to incorporate the latest advancements into cutting-edge hardware and/or software frameworks.
What We Need to See:
A minimum qualification of a master’s degree (or equivalent experience) in Computer Science, Artificial Intelligence, Applied Mathematics, or related fields.
Strong foundation in deep learning, with a particular emphasis on generative models.
A track record of at least 5 years of relevant software development experience in modern deep learning frameworks such as PyTorch.
Growth mindset and pragmatic attitude.
Ways to Stand Out from the Crowd:
Published research or noteworthy contributions to the field of deep learning, particularly around algorithm development for efficient deployment at scale.
Experience with benchmarking accuracy and performance of AI models.
Experience with CUDA programming and GPU performance optimizations.
Familiarity with computer architecture and how it relates to AI algorithms development.
You will also be eligible for equity and .
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