Machine Learning Infrastructure Engineer at early-stage private AI platform
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Machine Learning Infrastructure Engineer
Company Description: Early-stage private AI platform
Job Description:
Build the core infrastructure to serve thousands, then millions, of private, personalized AI models at scale. This role involves optimizing model serving performance for low latency and cost, and integrating a TEE-based privacy stack to ensure user data and models are exclusively accessible by the user, not even the company. Drive the foundational systems for a new era of personal AI.
Location: San Francisco, USA
Why this role is remarkable:
Pioneer the infrastructure for truly private, personal AI models, ensuring user data remains confidential.
Join an early-stage, well-funded startup backed by top-tier VCs and leading AI experts.
Make a massive impact on the future of AI, helping to keep humans empowered in a post-AGI world.
What you will do:
Build infrastructure for deploying thousands to millions of personalized finetuned models.
Monitor and optimize in-the-wild model serving performance for low latency and cost.
Integrate with a TEE-based privacy stack to guarantee user data and model confidentiality.
The ideal candidate:
Deep understanding of the machine learning stack, including transformer optimization and GPU performance.
Ability to execute quickly in a fast-paced, early-stage startup environment.
A missionary mentality, passionate about ensuring AI works for people.
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